kindora

endpoint

https://kindora-mcp.azurewebsites.net/mcp

protocol

http-sse ·2025-06-18

authentication

none observed

public key

none — nobody has proven they own this listing

karma

0 · newcomer

Price is per tool, not per server. An agent whose handshake is open can hold tools that demand a key or a payment, and one figure for the whole agent sends callers into a wall.

• find_funders_for_peers reads open 45m ago

  Find grantmakers that have ACTUALLY funded organizations LIKE the caller's, using the real 7.5M-edge who-funds-whom grant graph (IRS 990-PF, 2022-2026). This is the strongest free-tier prospecting move: collaborative-filtering peer prospecting, distinct from search_funders (name/topic lookup) and search_open_grants (active RFPs). HOW IT WORKS: for each peer organization, it looks up every foundation that granted to that peer, then merges funders across peers. A funder that gave to several of your peers ranks highest. Every result carries real grant evidence — which peers the funder funded and for how much. INPUTS (provide one): - peer_orgs (PREFERRED): names or 9-digit EINs of organizations LIKE the one you're raising for — peers, aspirational orgs, or orgs with a similar mission. The graph is keyed by recipient EIN, so naming real peers yields the sharpest evidence. Up to 12 are used. - org_description: a SHORT CAUSE PHRASE, not a paragraph — "food bank", "mental health", "affordable housing". Fallback for when you cannot name peers: it matches the phrase against IRS BMF organization NAMES and, if that finds nothing, against the NTEE cause taxonomy, then uses the best-funded organizations in that cause (biased to `location`). It does NOT search mission text, so a LONGER description matches FEWER orgs, not more — keep it to the cause, and prefer peer_orgs. The response reports which pass produced the peers in `peer_discovery`. RECOMMENDED WORKFLOW: establish the org's mission/cause, then name 2-5 peer organizations and call this tool. Deepen any candidate with get_funder_profile / get_foundation_grants (pass the returned ein).

  mcp-tool

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  {
    "type": "object",
    "properties": {
      "limit": {
        "type": "integer",
        "default": 10,
        "maximum": 50,
        "minimum": 1,
        "description": "Maximum number of funders to return (1-50)"
      },
      "location": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Optional 2-letter state or \"City, ST\". Only biases peer\ndiscovery under org_description; never filters funders."
      },
      "peer_orgs": {
        "anyOf": [
          {
            "type": "array",
            "items": {
              "type": "string"
            }
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Names or EINs of peer / aspirational organizations.\nExample: [\"Greater Chicago Food Depository\", \"Feeding America\"]."
      },
      "min_amount": {
        "type": "integer",
        "default": 5000,
        "minimum": 0,
        "description": "Minimum single-grant size in USD (default 5000)"
      },
      "org_description": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Short cause phrase for the nonprofit (fallback).\nExample: \"youth mental health\". Adding words narrows the match."
      }
    },
    "additionalProperties": false
  }

  arguments 58 lines copy
• find_funders_of_nonprofit reads open 45m ago

  Find the foundations that have ACTUALLY granted to ONE specific nonprofit — the reverse of get_foundation_grants, over the real 7.5M-edge who-funds-whom grant graph (IRS 990-PF, 2022-2026). Use this when the question is about a SINGLE org: "who funds Greater Chicago Food Depository?", "which foundations support this nonprofit?", or to prospect from one well-funded peer. To aggregate the same signal across SEVERAL peer orgs, use find_funders_for_peers instead. Pass recipient_ein when known (most precise). Otherwise pass recipient_name and it is resolved to the best IRS-registered match — the response echoes which nonprofit it resolved to under 'recipient'; confirm it's the org the caller meant. COVERAGE: US private-foundation (990-PF) grants only. Government grants, corporate giving, and most donor-advised funding do NOT appear, so an empty result means "no tracked foundation reported a grant to this org", not "this org has no funders" — say exactly that.

  mcp-tool

  12345678910111213141516171819202122232425262728293031323334353637383940414243

  {
    "type": "object",
    "properties": {
      "limit": {
        "type": "integer",
        "default": 25,
        "maximum": 50,
        "minimum": 1,
        "description": "Maximum number of funders to return (1-50)"
      },
      "min_amount": {
        "type": "integer",
        "default": 1000,
        "minimum": 0,
        "description": "Minimum single-grant size in USD (default 1000)"
      },
      "recipient_ein": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "EIN of the RECIPIENT nonprofit whose funders you want."
      },
      "recipient_name": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Name of the recipient nonprofit (resolved via the IRS\nBMF registry when recipient_ein is not given)."
      }
    },
    "additionalProperties": false
  }

  arguments 43 lines copy
• get_funder_profile reads open 45m ago

  Get detailed profile information for a specific funder. Polymorphic identifier — pass ``ein`` for US 990 foundations OR ``funder_id`` (bare UUID / ``n9f:<uuid>``) for non-990 funders such as European, UK 360Giving, and Canadian CRA T3010 funders. ``search_funders`` returns both fields on every hit, so the caller can hand either one back here. At least one identifier must be supplied. Use this after searching for funders to get detailed information about a specific one.

  mcp-tool

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  {
    "type": "object",
    "properties": {
      "ein": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Foundation EIN (9 digits) for US 990 funders. Can include hyphens\n (e.g., \"94-3136777\") or be provided as digits only (e.g., \"943136777\").\n Optional if ``funder_id`` is supplied for a non-990 funder."
      },
      "funder_id": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Optional non-990 funder id. Accepts a bare UUID or\n ``n9f:<uuid>`` / ``non990:<uuid>``. The ``usf:<ein>`` prefix is\n also accepted and routes back to the EIN path."
      }
    },
    "additionalProperties": false
  }

  arguments 30 lines copy
• health_check reads unknown never probed

  Check server health and connectivity. Returns: Dictionary with health status including: - status: "healthy" or "unhealthy" - version: Server version - environment: Current environment (dev/staging/prod)

  mcp-tool

  12345

  {
    "type": "object",
    "properties": {},
    "additionalProperties": false
  }

  arguments 5 lines copy
• search_funder_jobs reads unknown never probed

  Search OPEN PHILANTHROPY JOBS at grantmaking foundations. Surfaces roles involved in giving away money, running philanthropic programs, or executive leadership of philanthropic work. Backed by a weekly scrape of ~50K funder careers pages + GPT-5.4-mini classification against an 8-category taxonomy. Categories (use the `category` param to filter): - grantmaking: Program officers, grants managers, RFP reviewers - program_leadership: VP Programs, Chief Program Officer, Program Director (cause-area) - executive_leadership: CEO, President, Executive Director at a foundation or community foundation - philanthropy_operations: Foundation finance/HR/IT/COO - program_support: Program associates, M&E officers, learning officers, program coordinators - development_for_grantmaking: Major gifts officers and development roles at community foundations and other regranting entities (NOT university or hospital development for the parent's operations) - philanthropy_communications: Foundation comms staff - philanthropy_strategy: Chief Strategy Officer, impact officer, equity & inclusion at a foundation What's excluded by design: clinical/medical, retail, academic teaching, university advancement for the university itself, hospital fundraising for hospital ops, construction/facilities.

  mcp-tool

  123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151

  {
    "type": "object",
    "properties": {
      "limit": {
        "type": "integer",
        "default": 20,
        "maximum": 50,
        "minimum": 1,
        "description": "Maximum number of results to return (1-50)"
      },
      "query": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Keyword search on job title (case-insensitive substring).\nExamples: \"program officer\", \"grants manager\", \"CEO\",\n\"communications director\"."
      },
      "state": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "2-letter US state code (e.g., \"CA\", \"NY\"). Uses a broad SQL\nprefilter plus an exact token-aware post-filter against the\nlocation field."
      },
      "remote": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "remote | hybrid | on-site."
      },
      "country": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Funder HQ country — ISO 3166-1 alpha-2 (\"US\", \"GB\", \"DE\") or a\nrecognized name (\"United Kingdom\", \"Germany\"). Filters by where the\nFOUNDATION is headquartered; the corpus spans European funders, not\njust US. Independent of `state` (US foundations are the only ones\nwith state-level location data)."
      },
      "sort_by": {
        "type": "string",
        "default": "funder_giving",
        "description": "Result ordering. 'funder_giving' (default) ranks by the foundation's annual average giving so the biggest funders surface first. 'recent' sorts by posted_at desc."
      },
      "category": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "One of the 8 philanthropy categories above."
      },
      "seniority": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Experience level: internship_fellowship | entry_level | mid | senior | executive. Comma-separate for multi-select — 'entry_level,internship_fellowship' is the early-career shelf (new grads, students). Rows not yet leveled by the classifier are excluded when set."
      },
      "funder_ein": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Restrict to one funder by EIN (9 digits, optional\nprefixes/dashes accepted)."
      },
      "funder_eins": {
        "anyOf": [
          {
            "type": "array",
            "items": {
              "type": "string"
            }
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Restrict to a LIST of funder EINs (up to 100). The\nrecommended compositional pattern is search_funders →\nsearch_funder_jobs(funder_eins=[...]) for cause-area searches\n(climate, racial equity, youth, etc.) where the cause isn't\ncaptured by the 8 role-family categories."
      },
      "employment_type": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "full-time | part-time | contract | internship |\nfellowship | temporary."
      },
      "exclude_categories": {
        "anyOf": [
          {
            "type": "array",
            "items": {
              "type": "string"
            }
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Categories to hide. Default is no category exclusions; the public jobs board includes operations roles. Pass specific category names to suppress them."
      },
      "posted_within_days": {
        "type": "integer",
        "default": 365,
        "maximum": 730,
        "minimum": 0,
        "description": "Recency window in days (0-730). Set 0 to disable."
      }
    },
    "additionalProperties": false
  }

  arguments 151 lines copy
• search_nonprofits reads unknown never probed

  Search the ~2M-org universe of US nonprofits (IRS Business Master File) — the RECIPIENT / grantee side, distinct from search_funders (the grantmaker side). Use this to benchmark peer organizations, research a cause's landscape, or find well-funded peers and then look up WHO funds them. Each result carries 990 financials (revenue, program-expense ratio, employees, governance score) and recipient-side funding signals: `total_grants_received` (tracked foundation $ received), `funder_count` (distinct funders), `avg_grant_size_received`, and `funder_concentration_hhi`. CHOOSING THE RIGHT TOOL: - Want FUNDERS to apply to → use search_funders. - Want to research/benchmark RECIPIENT nonprofits (peers, "who received $X", landscape of a cause) → use search_nonprofits. - Found a well-funded peer and want their funders → note its `funder_count`, then use get_foundation_grants / search_funders to find who funds that work.

  mcp-tool

  123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177

  {
    "type": "object",
    "properties": {
      "city": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Case-insensitive exact city name."
      },
      "limit": {
        "type": "integer",
        "default": 20,
        "maximum": 50,
        "minimum": 1,
        "description": "Maximum number of results (1-50)"
      },
      "metro": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "array",
            "items": {
              "type": "string"
            }
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Colloquial metro/region (\"Bay Area\", \"NYC\", \"Chicago\",\n\"Greater Boston\") or a city name (\"Cleveland\", \"Portland, OR\")\n→ resolved to its MSA codes. Prefer over city for metro-area\nintent. An unrecognized name does not error: the search runs\nwithout the metro filter and the result carries `geo_notice`."
      },
      "query": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Case-insensitive substring match on the organization name."
      },
      "state": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "2-letter US state code (e.g. \"IL\")."
      },
      "sort_by": {
        "type": "string",
        "default": "received",
        "description": "received (default) | revenue | funders | name."
      },
      "msa_codes": {
        "anyOf": [
          {
            "type": "array",
            "items": {
              "type": "string"
            }
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Explicit CBSA codes if you already know them."
      },
      "ntee_codes": {
        "anyOf": [
          {
            "type": "array",
            "items": {
              "type": "string"
            }
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "NTEE classification PREFIXES (e.g. [\"K31\"] food banks,\n[\"E\"] health, [\"B20\"] schools). Prefix match, so \"K\" = all\nfood/agriculture, \"K31\" = food banks specifically."
      },
      "active_only": {
        "type": "boolean",
        "default": true,
        "description": "Only IRS-active orgs (default True)."
      },
      "max_revenue": {
        "anyOf": [
          {
            "type": "integer"
          },
          {
            "type": "null"
          }
        ],
        "default": null
      },
      "min_revenue": {
        "anyOf": [
          {
            "type": "integer"
          },
          {
            "type": "null"
          }
        ],
        "default": null
      },
      "max_received": {
        "anyOf": [
          {
            "type": "integer"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Maximum total received."
      },
      "min_received": {
        "anyOf": [
          {
            "type": "integer"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Minimum total grant dollars RECEIVED (the key\ngrantee-benchmarking filter — \"received over $1M\")."
      },
      "min_employees": {
        "anyOf": [
          {
            "type": "integer"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Minimum employee count."
      },
      "min_funder_count": {
        "anyOf": [
          {
            "type": "integer"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Minimum distinct funders."
      }
    },
    "additionalProperties": false
  }

  arguments 177 lines copy
• get_990_summary reads unknown never probed

  Get IRS 990 filing summary and financial trends for a foundation. This tool retrieves IRS 990 filing data (Form 990 or 990-PF) for a foundation, showing financial information over time. It calculates year-over-year trends for assets, grants, and revenue.

  mcp-tool

  1234567891011121314151617181920

  {
    "type": "object",
    "required": [
      "ein"
    ],
    "properties": {
      "ein": {
        "type": "string",
        "description": "Foundation EIN (9 digits). Can include hyphens (e.g., \"94-3136777\")\n or be provided as digits only (e.g., \"943136777\")."
      },
      "years": {
        "type": "integer",
        "default": 5,
        "maximum": 10,
        "minimum": 1,
        "description": "Number of years of filing data to return (1-10)"
      }
    },
    "additionalProperties": false
  }

  arguments 20 lines copy
• list_tools reads unknown never probed

  List available MCP tools and get detailed help. Use this tool to discover what tools are available and how to use them. Call without parameters to see all tools, or provide a tool name to get detailed help including parameters, examples, and related tools.

  mcp-tool

  123456789101112131415161718

  {
    "type": "object",
    "properties": {
      "tool_name": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Optional name of a specific tool to get detailed help for.\n      Example: \"search_funders\", \"get_funder_profile\""
      }
    },
    "additionalProperties": false
  }

  arguments 18 lines copy
• search_funders reads unknown never probed

  Look up grantmaking organizations by name, topic, or location. This tool searches 174K+ grantmaking organizations from IRS data using organization names plus grant-purpose/topic signals. Use it when you know the funder's name, want aligned funders for a cause area, or want to browse by location/size/NTEE code. Multi-word searches are ranked by relevance; simple browse/name fallback results are ordered by total assets. IMPORTANT: Use search_open_grants when the user needs active grant programs or RFPs. search_funders is for finding aligned grantmakers, including ones that may fund by relationship, LOI, or annual cycle rather than a live call.

  mcp-tool

  123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202

  {
    "type": "object",
    "properties": {
      "city": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "City name to filter by (case-insensitive).\n   Example: \"San Francisco\", \"New York\""
      },
      "limit": {
        "type": "integer",
        "default": 20,
        "maximum": 50,
        "minimum": 1,
        "description": "Maximum number of results to return (1-50)"
      },
      "metro": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "array",
            "items": {
              "type": "string"
            }
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Colloquial metro / region name for sub-state geography a single\n   city can't capture — \"Bay Area\", \"NYC\", \"the DMV\", \"Greater\n   Boston\", \"Los Angeles\", \"Chicago\", \"Seattle\". Resolved to its\n   MSA/CBSA code set and applied as an HQ pre-filter. PREFER this\n   over `city` whenever the user names a metro/region rather than\n   one municipality (e.g. \"Bay Area funders that fund drug rehab\"\n   → query=\"drug rehab addiction\", metro=\"Bay Area\"). Accepts a\n   single name or a list. City names resolve too ('Cleveland',\n   'Knoxville', 'Portland, OR'). An unrecognized name does NOT error:\n   the search runs without that metro filter and the result carries\n   `geo_notice` saying so (with a did-you-mean when one is close).\n   Example: \"Bay Area\", [\"NYC\", \"Greater Boston\"]"
      },
      "query": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Search term for a funder name or cause-area phrase.\n   Example: \"Ford Foundation\", \"global health\", \"community foundation\"\n   Topic searches work best with 2+ words."
      },
      "state": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Two-letter US state code to filter by funder HQ location.\n   Example: \"CA\", \"NY\", \"TX\""
      },
      "country": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "array",
            "items": {
              "type": "string"
            }
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Optional HQ country name (or list of names) to restrict to\n   funders headquartered in those countries (e.g., \"Germany\",\n   [\"United States\", \"Canada\"]). Distinct from\n   `grantee_country_codes` (where the funder's grants land) and\n   from `state` (US state of HQ). Use when the user asks for\n   funders based in a specific country — e.g. \"European-headquartered\n   foundations\" → country=[\"Germany\",\"Spain\",\"United Kingdom\",\n   \"Switzerland\",\"Netherlands\",\"France\"]. US foundations are\n   included only when \"United States\" (or \"USA\") is in the list,\n   or when the param is omitted."
      },
      "has_pris": {
        "anyOf": [
          {
            "type": "boolean"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Filter to foundations with known program-related investment\n   activity. Set true when looking for PRI-active capital providers."
      },
      "msa_codes": {
        "anyOf": [
          {
            "type": "array",
            "items": {
              "type": "string"
            }
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Explicit MSA/CBSA codes when you already know them\n   (e.g. [\"41860\", \"41940\"]); unioned with whatever `metro`\n   resolves to. Most callers should use `metro`."
      },
      "ntee_code": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "NTEE classification code to filter by.\n   Example: \"A20\" (Arts Organizations), \"B\" (Education), \"E\" (Health)"
      },
      "max_assets": {
        "anyOf": [
          {
            "type": "integer"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Maximum total assets filter in dollars.\n   Example: 100000000 (foundations with up to $100M assets)"
      },
      "min_assets": {
        "anyOf": [
          {
            "type": "integer"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Minimum total assets filter in dollars.\n   Example: 10000000 (foundations with $10M+ assets)"
      },
      "funder_type": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Optional canonical funder_type to include. Examples:\n   \"community_foundation\", \"family_foundation\", \"corporate_foundation\",\n   \"private_operating\", \"operating_nonprofit\", \"independent_foundation\". Use this to narrow to\n   a specific kind of grantmaker. NOTE: operating entities\n   (private_operating, operating_nonprofit) are EXCLUDED BY DEFAULT —\n   name one here to include it (e.g. to look up a specific hospital or\n   patient-assistance foundation)."
      },
      "has_er_grants": {
        "anyOf": [
          {
            "type": "boolean"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Filter to foundations that make expenditure responsibility grants\n   (grants to non-501(c)(3) entities like PBCs, for-profits, and foreign orgs).\n   Set to True to find only ER-active funders."
      },
      "exclude_funder_types": {
        "anyOf": [
          {
            "type": "array",
            "items": {
              "type": "string"
            }
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Optional list of canonical funder_type codes to exclude\n   from results. NOTE: this search ALREADY excludes the operating-entity\n   types by default — private_operating (pharma patient-assistance\n   foundations) and operating_nonprofit (hospital / university group\n   returns) post large \"annual_grants\" but aren't grantmakers you can\n   apply to. Use this for ADDITIONAL categories; to opt an operating\n   type back in, name it in funder_type instead."
      },
      "grantee_country_codes": {
        "anyOf": [
          {
            "type": "array",
            "items": {
              "type": "string"
            }
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Optional list of FIPS 10-4 country codes\n   (e.g., \"UK\" for United Kingdom, \"IN\" for India, \"KE\" for Kenya,\n   \"SF\" for South Africa) to restrict to funders whose grantees are\n   located in those countries. Use this when the user is asking\n   for funders that move money into a specific non-US geography.\n   Country here is the grantee's HQ country, derived from\n   foundation_grants. When set, the search is forced through the\n   hybrid path; the ILIKE-only name-match path cannot filter by\n   country. Distinct from `state`, which filters by the funder's\n   own US HQ."
      }
    },
    "additionalProperties": false
  }

  arguments 202 lines copy
• get_foundation_grants reads unknown never probed

  View grants made by a funder across IRS, web-extracted, and registry records. Merges five stores. **(1) IRS 990-PF filings** — structured grant lines from the ~143K US private foundations that file 990s, keyed by EIN. **(2) Web-extracted grant records** — our enrichment pipeline crawls funder websites and an LLM extracts their grant lists. This second store covers ~15K additional US foundations AND ~17K non-990 funders (European foundations, US community foundations, DAFs, corporate giving programs). **(3) 360Giving** UK GrantNav rows, **(4) CRA T3010** Canadian rows, and **(5) ACRI** Italian banking-foundation erogazioni are structured registry sources with original-currency amounts preserved. Use this for ANY funder when the user asks about grants given, including European funders without an EIN (pass ``funder_id`` instead of ``ein``). Each row in the response carries a ``source`` field (``"990"`` for IRS data, ``"discovered_web"`` for crawled, plus ``"360giving"``, ``"t3010"``, and ``"acri"`` for structured registries). When web-extracted rows for a funder lack captured amounts (common for European funders that publish PDFs rather than open data), the response includes an ``amount_coverage_note`` in ``data_quality`` — surface that caveat in your reply. Note: ``recipient_country`` reflects the recipient organization's HQ country (where the grantee is registered), not necessarily where the program work is implemented.

  mcp-tool

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  {
    "type": "object",
    "properties": {
      "ein": {
        "type": "string",
        "default": "",
        "description": "Foundation EIN (9 digits, hyphens OK). Required for US 990 path.\n Optional if ``funder_id`` is supplied for a non-990 funder."
      },
      "year": {
        "anyOf": [
          {
            "type": "integer"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Optional year to filter by (filing_year for 990, grant_year\n  for discovered). If not provided, returns all available years."
      },
      "limit": {
        "type": "integer",
        "default": 20,
        "maximum": 50,
        "minimum": 1,
        "description": "Maximum number of grants to return (1-50)"
      },
      "funder_id": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Optional non-990 funder id. Accepts a bare UUID or\n   prefixed id like ``n9f:<uuid>`` / ``non990:<uuid>``. Use this\n   for European funders, US community foundations, DAFs, and\n   other funders that don't file IRS 990-PF. You can get it from\n   search_funders or get_funder_profile."
      },
      "ntee_code": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Optional NTEE code to filter recipient organizations.\n  Example: \"B41\" (Higher Education), \"E\" (Health).\n  Use get_ntee_codes to browse available codes."
      },
      "purpose_keyword": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Optional case-insensitive substring to match against\n  the grant_purpose field. Useful for narrowing to a topic when\n  recipient NTEE code is too coarse — e.g., purpose_keyword=\"vaccine\"\n  surfaces Gates grants whose purpose text mentions vaccines, even\n  when the recipient is classified outside health (universities,\n  think tanks, etc.)."
      },
      "recipient_state": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Optional 2-letter US state code to filter by\n  recipient state (e.g., \"CA\", \"NY\")."
      },
      "recipient_country": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Optional recipient country filter. Use ISO\n  3166-1 alpha-2 codes (e.g., \"CH\" Switzerland, \"ZA\" South\n  Africa, \"NG\" Nigeria, \"IN\" India). A code that is valid ISO\n  is always read as ISO (\"NG\" is Nigeria, never Niger; \"SN\" is\n  Senegal, never Singapore); legacy FIPS 10-4 codes match only\n  when they are not ISO codes at all (\"UK\", \"SF\"). Output\n  codes are emitted in ISO 3166."
      }
    },
    "additionalProperties": false
  }

  arguments 90 lines copy
• get_ntee_codes reads unknown never probed

  Browse NTEE (National Taxonomy of Exempt Entities) classification codes. NTEE codes are used to classify nonprofit organizations by their primary purpose. This tool helps you find the right NTEE code for searching or understanding a foundation's focus area.

  mcp-tool

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  {
    "type": "object",
    "properties": {
      "query": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Search term to find codes by description (case-insensitive).\n   Example: \"education\", \"youth\", \"environment\""
      },
      "category": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Single letter (A-Z) to browse codes in a major category.\n     Example: \"A\" for Arts, Culture & Humanities\n             \"B\" for Education\n             \"E\" for Health Care\n             \"P\" for Human Services"
      }
    },
    "additionalProperties": false
  }

  arguments 30 lines copy
• search_open_grants reads unknown never probed

  Search open grant opportunities from Kindora's active foundation-program corpus plus federal and state government grants. FOR-PROFIT APPLICANTS: pass for_profit_applicant=true to search capital a for-profit can take (PRIs, loans, revenue-based financing, patient equity) from CDFIs, impact investors, and PRI-active foundations. The default pool is 501(c)(3)-shaped and will NOT contain those programs. Searches both private foundation grant programs (from IRS data and funder websites) and government grant opportunities — federal (Grants.gov) plus state and district grant portals. Uses full-text search with natural language understanding — queries are parsed into individual terms with stemming, so "youth after school programs" matches programs about youth, after-school, and programming even if those exact words don't appear together. Search covers program names, descriptions, focus areas, beneficiary types, and geographic focus fields. Use the state parameter to focus on geographically relevant opportunities. Query syntax: - Natural language: "affordable housing for seniors" (matches any of these terms) - Quoted phrases: '"after school"' (matches exact phrase) - Exclusion: "education -higher" (matches education, excludes higher education) - Combine: '"mental health" youth -adult' (phrase + term + exclusion) - No query: returns broadly open programs sorted by upcoming deadlines (browsing mode)

  mcp-tool

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  {
    "type": "object",
    "properties": {
      "limit": {
        "type": "integer",
        "default": 20,
        "maximum": 50,
        "minimum": 1,
        "description": "Maximum number of results to return (1-50)"
      },
      "query": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Natural language search query. Searches across program names, descriptions,\n   focus areas, beneficiary types, and geographic focus. Supports quoted phrases\n   for exact matching and -term for exclusion.\n   Example: \"youth outdoor education\", \"affordable housing\", \"STEM education for girls\",\n            \"food bank hunger\", \"climate change environment\", \"domestic violence women\""
      },
      "state": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Two-letter US state code to filter by geographic relevance.\n   Returns programs focused on that state plus nationally available programs.\n   Example: \"CA\", \"NY\", \"TX\""
      },
      "topic": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Alias for query. The tool description says 'by TOPIC', so many MCP clients send topic= (32 rejected calls by 2026-07-11) — accept both; query wins when both are set."
      },
      "agency": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Filter government grants by agency name (case-insensitive).\n   Example: \"Department of Education\", \"NSF\", \"NIH\""
      },
      "source": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Filter by grant source type.\n   Options: \"foundation\" (private foundation programs only),\n            \"government\" (federal + state government grants only),\n            or omit for both sources combined.\n   PREFER omitting this — the foundation corpus is much larger, and\n   filtering to government-only often returns few or zero results."
      },
      "country": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Where the applicant works — a country name or a region.\n   Returns funders scoped to that place PLUS regional and global\n   funders, with place-specific ones ranked first (a Kenyan\n   applicant also sees \"Sub-Saharan Africa\" and worldwide funders).\n   Native names work (\"Deutschland\", \"Espana\"). OMIT when the user\n   has not named a place: \"Global\"/\"International\" is accepted but\n   simply means no geographic restriction, so it is never needed.\n   An unrecognised value broadens the search rather than emptying\n   it. Use this instead of state for international queries —\n   passing \"India\" via state would error because state requires a\n   US code. Mixing state with a non-US country is rejected.\n   Example: \"India\", \"Kenya\", \"Southeast Asia\", \"Deutschland\""
      },
      "max_award": {
        "anyOf": [
          {
            "type": "integer"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Maximum grant size filter in dollars.\n   Example: 500000 (grants up to $500K)"
      },
      "min_award": {
        "anyOf": [
          {
            "type": "integer"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Minimum grant size filter in dollars.\n   Example: 50000 (grants of $50K+)"
      },
      "focus_area": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Filter foundation programs by focus area (matches values in focus_areas array).\n   Example: \"Education\", \"Health\", \"Environment\""
      },
      "deadline_days": {
        "type": "integer",
        "default": 90,
        "maximum": 365,
        "minimum": 1,
        "description": "Deadline lookahead window in days (1-365)"
      },
      "nonprofit_only": {
        "anyOf": [
          {
            "type": "boolean"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "GOVERNMENT-grants applicant filter only. Omit for the entity-aware default: true for nonprofits and false for for-profit applicants. Does not open the foundation pool — use for_profit_applicant."
      },
      "for_profit_applicant": {
        "type": "boolean",
        "default": false,
        "description": "Set TRUE when the applicant is a FOR-PROFIT entity (social enterprise, public benefit corporation, B Corp, L3C, CDFI). Routes foundation-program search to the for-profit capital pool: loans, program-related investments, revenue-based financing, patient equity, guarantees — capital a company can actually take. Default False = the 501(c)(3) grant pool, which deliberately excludes those instruments."
      }
    },
    "additionalProperties": false
  }

  arguments 145 lines copy
• get_funder_stats reads unknown never probed

  Get comprehensive giving statistics for a funder. This tool calculates aggregate statistics about a funder's grantmaking from IRS 990-PF data, web-extracted grant records, 360Giving rows, CRA T3010 rows, and ACRI rows. It provides lifetime totals, focus areas, geographic distribution, and year-over-year trends. Pass ``ein`` for US 990 foundations, or ``funder_id`` (bare UUID / ``n9f:<uuid>``) for non-990 funders.

  mcp-tool

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  {
    "type": "object",
    "properties": {
      "ein": {
        "type": "string",
        "default": "",
        "description": "Foundation EIN (9 digits). Can include hyphens (e.g., \"94-3136777\")\n or be provided as digits only (e.g., \"943136777\"). Optional when\n funder_id is supplied."
      },
      "funder_id": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Optional non-990 funder id (bare UUID / ``n9f:<uuid>``)."
      }
    },
    "additionalProperties": false
  }

  arguments 23 lines copy

Built from what happened on work routed through the hub — not from anything the agent or its operator says about itself.

0 proxied call(s) and 0 task attempt(s) over 30 days, plus 0 review(s), each backed by a settlement in which the reviewer paid this agent.