vc-deal-flow-signal
https://signals.gitdealflow.com
Registry code: f694de06f995222e
VC Deal Flow Signal, deep_signal lookup (commit velocity, contributor growth, sector rank, thesis sentence) for one named startup. Misses return 404 with no settlement.
from a public catalogue that lists it, not from the operator
- endpoint
- https://signals.gitdealflow.com/api/mcp/rpc
- door code
- ebd27c83469c1c78
- protocol
- streamable-http ·2025-06-18
- authentication
- none observed
- public key
- none — nobody has proven they own this listing · is it yours? claim it
- karma
- 0 · newcomer
- Is vc-deal-flow-signal live?
- Yes — it answered the hub's last check (checked 1h ago). It answered 99% of checks over the last 30 days.
- Is vc-deal-flow-signal free to use?
- Yes — the hub reached it with no key and no payment.
- What tools does vc-deal-flow-signal have?
- 12 tools: get_signals_summary, compare_signals, get_startup_signal, get_diligence_dossier, shortlist_signals, get_scout_receipts, search_startups_by_sector, get_deep_signal, ….
- Is vc-deal-flow-signal safe to connect?
- The hub found no text in its card or tool descriptions aimed at the agent reading them. It measures what the server answers, not its code — grant it only the access its tools need.
90 days 99.2%· all time 99.5%
last good check
of 12 tools
- degraded → live
- live → degraded· timeout after 20000ms
- degraded → live
- live → degraded· timeout after 20000ms
- degraded → live
- used for
- get startup engineering acceleration signals
- predict startup funding likelihood
- compare startups
- get diligence dossier on a company
- list trending startups by sector
- takes → gives
- text → data
- tools
- 12 reads
Calls placed through this hub's router, from its own receipts. Every caller and every payer counts the same; the chain total is counted from three payers.
through this hub
successful
what callers paid
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.
predict_funding reads open 23h ago
Transparent, scored funding-likelihood claim for one tracked startup, with the full evidence chain and citable provenance. Instead of an opaque number, returns the score, every component that produced it, a confidence level, honest caveats, and links to the methodology + SSRN paper so the derivation can be cited. IS a deterministic heuristic over public GitHub engineering-acceleration signals; IS NOT an ML black box, a guarantee of any financing event, or based on private/cap-table data. The disclaimer is returned in every response. SCORING (also returned in evidence.scoreBreakdown): velocity ≤40 (saturates +300%), contributorGrowth ≤25 (saturates +200%), newRepos ≤15 (saturates 10), signalType ≤20 (Deploy frequency spike 20 / Engineering hiring burst 17 / Infrastructure buildout 14 / Framework migration 8). Total 0-100 → >=70 high, 45-69 elevated, 25-44 moderate, <25 low. PARAMETERS: { name }, display name or GitHub org slug (case-insensitive). On no match returns { found: false, suggestion } (expected, not an error).
{ "type": "object", "required": [ "name" ], "properties": { "name": { "type": "string", "maxLength": 100, "minLength": 1, "description": "Startup display name or GitHub org slug. Case-insensitive." } }, "additionalProperties": false }arguments 15 linesget_trending_startups reads open 6h ago
Top 20 startups by engineering acceleration across all 20 sectors for the current weekly period. Read-only, idempotent.
{ "type": "object", "properties": {}, "additionalProperties": false }arguments 5 linesget_methodology reads open 13h ago
Full methodology document covering data sources, metric computation, signal classification thresholds, refresh cadence, and known limitations.
{ "type": "object", "properties": {}, "additionalProperties": false }arguments 5 linesget_signals_summary reads unknown never probed
Period, sector and startup counts, last refresh, citation, and direct URLs to every machine-readable format.
{ "type": "object", "properties": {}, "additionalProperties": false }arguments 5 linescompare_signals reads unknown never probed
Score and rank 2-5 named startups side by side, returning each one's acceleration score, evidence, and raise-likelihood band plus a single recommendation for which warrants deeper diligence. Same transparent scoring as predict_funding / shortlist_signals. Names that don't resolve are returned in `notFound` (expected, not an error). The recommendation is computed only over resolved companies; if fewer than 2 resolve it explains that no comparison was possible. PARAMETERS: { names: string[] }, 2 to 5 display names or GitHub org slugs (case-insensitive).
{ "type": "object", "required": [ "names" ], "properties": { "names": { "type": "array", "items": { "type": "string", "maxLength": 100, "minLength": 1 }, "maxItems": 5, "minItems": 2 } }, "additionalProperties": false }arguments 19 linesget_startup_signal reads unknown never probed
Full engineering-acceleration profile for a single tracked startup, by display name or GitHub org slug. Case-insensitive, normalization-tolerant.
{ "type": "object", "required": [ "name" ], "properties": { "name": { "type": "string", "examples": [ "roboflow", "SkyPilot", "Supabase", "Hugging Face" ], "maxLength": 100, "minLength": 1, "description": "Startup display name OR GitHub org name. Case-insensitive; punctuation and whitespace are ignored during matching." } }, "additionalProperties": false }arguments 21 linesget_diligence_dossier reads unknown 6h ago
Public-source diligence dossier for a company or entity in one cited object: who acquired it (M&A history), which funds publicly backed it, and its published engineering-acceleration signal. Use mid-diligence for 'who acquired X', 'which funds backed Y', 'what's the signal on Z'. Sources are press-release / SEC-filing / both-sides-disclosed only; returns found:false (an expected outcome, not an error) with honest notes when the entity is outside the tracked corpus, never guesses.
{ "type": "object", "required": [ "company" ], "properties": { "company": { "type": "string", "examples": [ "Figma", "Supabase", "Broadcom", "Auth0" ], "maxLength": 100, "minLength": 1, "description": "Company or entity name (target, acquirer, or tracked startup). Case-insensitive, normalization-tolerant." } }, "additionalProperties": false }arguments 21 linesshortlist_signals reads unknown never probed
Return a ranked shortlist of the strongest engineering-acceleration signals matching a set of filters, the whole sourcing workflow in ONE call (e.g. 'the 5 strongest signals in healthcare in the EU'). Scans the full tracked universe, scores each with the transparent engine (same scoring as predict_funding), filters, sorts by accelerationScore desc, returns the top `limit`. GEOGRAPHY IS REGION-LEVEL ONLY, values are US / EU / UK / APAC / LATAM / Canada / Unknown. City/country aliases ('NYC', 'New York', 'London', 'Berlin', 'Singapore') normalize up to the enclosing region and the response `notes` says so. There is no city-level filtering. PARAMETERS (all optional): sector (one of 20 slugs), geography (region token or alias), signalType (exact label), minAccelerationScore (0-100), minVelocityChangePct (integer percent), limit (1-25, default 5).
{ "type": "object", "properties": { "limit": { "type": "integer", "default": 5, "maximum": 25, "minimum": 1 }, "sector": { "enum": [ "ai-ml", "fintech", "climate-tech", "developer-tools", "cybersecurity", "healthcare", "edtech", "ecommerce-infrastructure", "supply-chain", "web3", "enterprise-saas", "data-infrastructure", "robotics", "legal-tech", "hr-tech", "proptech", "agtech", "gaming", "space-tech", "social-community" ], "type": "string" }, "geography": { "type": "string", "description": "Region token (US/EU/UK/APAC/LATAM/Canada) or a city/country alias normalized up to the region." }, "signalType": { "enum": [ "Deploy frequency spike", "Engineering hiring burst", "Infrastructure buildout", "Framework migration" ], "type": "string" }, "minAccelerationScore": { "type": "integer", "maximum": 100, "minimum": 0 }, "minVelocityChangePct": { "type": "integer" } }, "additionalProperties": false }arguments 58 linesget_scout_receipts reads unknown 6h ago
Compute a Scout Score (0-100) for a GitHub user from their public starring history. Cross-references starred repos against ~75 validated unicorns and grades how many they starred *before* the validation event. Returns score, rank (curious/scout/sharp/elite/oracle), top early calls, personality summary, and a shareable card URL.
{ "type": "object", "required": [ "github_username" ], "properties": { "github_username": { "type": "string", "pattern": "^[a-zA-Z0-9](?:[a-zA-Z0-9]|-(?=[a-zA-Z0-9])){0,38}$", "examples": [ "torvalds", "kindrat86", "tj" ], "maxLength": 39, "minLength": 1, "description": "GitHub username, 1-39 chars, alphanumeric + single hyphens." } }, "additionalProperties": false }arguments 21 linessearch_startups_by_sector reads unknown 23h ago
Every tracked startup within a sector, ranked by engineering acceleration. Sector slug must be one of 20 enumerated values.
{ "type": "object", "required": [ "sector" ], "properties": { "sector": { "enum": [ "ai-ml", "fintech", "climate-tech", "developer-tools", "cybersecurity", "healthcare", "edtech", "ecommerce-infrastructure", "supply-chain", "web3", "enterprise-saas", "data-infrastructure", "robotics", "legal-tech", "hr-tech", "proptech", "agtech", "gaming", "space-tech", "social-community" ], "type": "string", "examples": [ "healthcare", "web3", "gaming", "edtech" ], "description": "Sector slug from the enumerated list. Map fuzzy user input to the closest slug (e.g. 'crypto' → 'web3', 'SaaS' → 'enterprise-saas')." } }, "additionalProperties": false }arguments 41 linesget_deep_signal reads unknown never probed
PAID per-request, €0.19/call, 100 credits = €19 at https://signals.gitdealflow.com/agents/credits. Returns enriched signal beyond the free get_startup_signal: composite score (0-100), velocity/growth/novelty sub-scores, in-sector rank + percentile, plain-English investment thesis, top-3 sector comparables, and multi-period history. Requires Authorization: Bearer gdf_v2.cus_xxx.<hmac>. 1 credit consumed only on a successful match; misses are FREE. Credits never expire.
{ "type": "object", "required": [ "name" ], "properties": { "name": { "type": "string", "maxLength": 100, "minLength": 1, "description": "Startup display name or GitHub org slug." } }, "additionalProperties": false }arguments 15 linesshare_result reads unknown 23h ago
Generate a ready-to-share social-media post (tweet, Bluesky, Mastodon, LinkedIn, Telegram) about a result the user just received from another VC Deal Flow Signal tool, plus the install command for the MCP server. Returns the post body, character counts per platform, and one-click intent URLs to compose the post in each network. WHEN TO USE: - The user just got a `get_trending_startups` / `search_startups_by_sector` / `get_startup_signal` / `get_deep_signal` result and says 'share this', 'tweet this', 'post this', or 'how do I tell people about this?'. - The user is writing a thread/post about startup engineering signals and wants the canonical install command + share copy. DO NOT USE FOR: - Posting on the user's behalf, this tool only composes the text + intent URLs. The user must click and confirm in the destination network. - Generating fake or speculative results, pass real data the agent received from another tool call. BEHAVIOR (two-step approval flow, see `approval_token`): - Step 1: call this tool with `summary` only. The server replies with an error (-32602) containing a `/share-approve?summary=...` URL the user must open. - Step 2: the user reads the proposed summary on that page, clicks Approve, and pastes the resulting 10-minute token back into the chat. Retry the tool with `approval_token` filled in and the SAME `summary` verbatim. - The token is bound to a hash of `summary`; if the agent rewrites the summary between approval and the retry, the call is rejected. - Composes platform-specific posts (Twitter ≤275 chars, Bluesky ≤295, Mastodon ≤495, LinkedIn ≤695, Telegram ≤995) with a consistent hook + insight + install URL. - Returns intent URLs (e.g. https://x.com/intent/post?text=...) so the user/agent can open the destination network with the post pre-filled. - Always includes the canonical install command `npx @gitdealflow/mcp-signal` and the SSRN paper link for credibility. PARAMETERS: - `summary` (string, required, 10-200 chars), the one-line takeaway to share. - `approval_token` (string, required after first call), the 10-minute token returned by the /share-approve page. - `network` (string, optional), 'twitter' | 'bluesky' | 'mastodon' | 'linkedin' | 'telegram' | 'all' (default: 'all'). - `mention_handle` (boolean, optional, default false), include @sipiteno attribution (twitter/bluesky/mastodon only).
{ "type": "object", "required": [ "summary", "approval_token" ], "properties": { "network": { "enum": [ "twitter", "bluesky", "mastodon", "linkedin", "telegram", "all" ], "type": "string", "default": "all", "description": "Target network. 'all' returns one post per network." }, "summary": { "type": "string", "maxLength": 200, "minLength": 10, "description": "One-line takeaway (10-200 chars) the user wants to share." }, "approval_token": { "type": "string", "maxLength": 512, "minLength": 16, "description": "10-minute HMAC-signed token bound to a hash of `summary`. Obtain it by directing the user to https://signals.gitdealflow.com/share-approve?summary=<urlencoded-summary>they review and click Approve, then paste the resulting token back. The first call with no token will return an error containing the exact URL to send the user to." }, "mention_handle": { "type": "boolean", "default": false, "description": "Include @sipiteno attribution. Only applied to twitter/bluesky/mastodon." } }, "additionalProperties": false }arguments 40 lines
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- settled without a human
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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.
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- gitdealflow.com gitdealflow-mcp