fermi

endpoint

https://fermi.kromatic.com/mcp/v1

protocol

http-sse ·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 fermi live?

Yes — it answered the hub's last check (checked 50m ago). It answered 100% of checks over the last 30 days.

Is fermi free to use?

Not measured yet.

What tools does fermi have?

3 tools: buy_credits, estimate, feedback.

Is fermi 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.

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.

• buy_credits unknown never probed

  Purchase credits using a saved payment method (off-session). Requires a prior Stripe Checkout session to have saved a card. Credits are $0.50 each. Use GET /api/v1/billing/pricing to confirm the current price. Args: credits: Number of credits to purchase (minimum 1). api_key: Your Fermi API key from POST /api/v1/accounts. Required. Returns: Dict with credits_purchased, new_balance, and payment_status. Raises: ToolError: if authentication fails, no payment method is on file, or the card is declined.

  mcp-tool

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  {
    "type": "object",
    "title": "buy_creditsArguments",
    "required": [
      "credits",
      "api_key"
    ],
    "properties": {
      "api_key": {
        "type": "string",
        "title": "Api Key"
      },
      "credits": {
        "type": "integer",
        "title": "Credits"
      }
    }
  }

  arguments 18 lines copy
• estimate unknown never probed

  Return a calibrated probability distribution for a natural-language question. Args: question: The natural-language question (e.g. "What will the price of Bitcoin be in 6 months?"). unit: The unit the answer should be expressed in (e.g. "USD", "people", "meters"). target_horizon: When the estimate applies (e.g. "6 months", "2030", "current"). disclaimer_acknowledged: Must be true. Confirms you understand estimates are probabilistic decision-support only, not financial/medical/legal advice. requested_tier_id: Tier (1=fast sync, 2=grounded sync, 3=deep research async). Default 1. context: Optional extra context to condition the estimate. coverage_probability: Width of the confidence interval (0, 1). Default 0.9 (90% CI). source_inputs: Optional list of structured inputs (files, tables) for the model to consider. Each item needs source_type ("qualitative_text", "spreadsheet", or "structured_file") and either content (text) or structured_data (dict/list). callback_url: Optional webhook URL. When set, the completed or failed result is POSTed here with an HMAC signature, so you don't need to poll for async tiers. api_key: Your Fermi API key from POST /api/v1/accounts. Omit to use the anonymous tier. provider: Optional LLM provider selector ("openai" or "anthropic"). When omitted the server uses its configured default. Tier 1 supports both providers; tiers 2-3 currently accept "openai" only. model: Optional model id for the selected provider. Must match the model configured for (tier_id, provider); omit to accept the default. Returns: EstimateSuccessResponse as a dict: estimation_interval, distribution_family, distribution_parameters, point_estimate, reasoning_summary, assumptions, credits_charged, disclaimer, provider, and model. Raises: ToolError: if the estimate service rejects the request (bad tier, out of credits, unknown provider, missing disclaimer acknowledgement).

  mcp-tool

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  {
    "type": "object",
    "title": "estimateArguments",
    "required": [
      "question",
      "unit",
      "target_horizon",
      "disclaimer_acknowledged"
    ],
    "properties": {
      "unit": {
        "type": "string",
        "title": "Unit"
      },
      "model": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "title": "Model",
        "default": null
      },
      "api_key": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "title": "Api Key",
        "default": null
      },
      "context": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "title": "Context",
        "default": null
      },
      "provider": {
        "anyOf": [
          {
            "enum": [
              "openai",
              "anthropic"
            ],
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "title": "Provider",
        "default": null
      },
      "question": {
        "type": "string",
        "title": "Question"
      },
      "callback_url": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "title": "Callback Url",
        "default": null
      },
      "source_inputs": {
        "anyOf": [
          {
            "type": "array",
            "items": {
              "type": "object",
              "additionalProperties": true
            }
          },
          {
            "type": "null"
          }
        ],
        "title": "Source Inputs",
        "default": null
      },
      "target_horizon": {
        "type": "string",
        "title": "Target Horizon"
      },
      "requested_tier_id": {
        "type": "integer",
        "title": "Requested Tier Id",
        "default": 1
      },
      "coverage_probability": {
        "type": "number",
        "title": "Coverage Probability",
        "default": 0.9
      },
      "disclaimer_acknowledged": {
        "type": "boolean",
        "title": "Disclaimer Acknowledged"
      }
    }
  }

  arguments 118 lines copy
• feedback unknown never probed

  Submit feedback, a feature request, or a bug report to the Fermi team. An email is sent to the team and a copy is sent to the address you provide. Args: feedback_type: One of "feedback", "feature_request", or "bug". message: Your feedback or request (10-5000 characters). Be specific. sender_email: Your email address. A confirmation copy is sent here. sender_name: Your name (optional). api_key: Your Fermi API key (optional). If provided, your account ID is attached to the message for context. Returns: Confirmation with status "sent". Raises: ToolError: if validation fails or email delivery fails.

  mcp-tool

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  {
    "type": "object",
    "title": "feedbackArguments",
    "required": [
      "feedback_type",
      "message",
      "sender_email"
    ],
    "properties": {
      "api_key": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "title": "Api Key",
        "default": null
      },
      "message": {
        "type": "string",
        "title": "Message"
      },
      "sender_name": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "title": "Sender Name",
        "default": null
      },
      "sender_email": {
        "type": "string",
        "title": "Sender Email"
      },
      "feedback_type": {
        "enum": [
          "feedback",
          "feature_request",
          "bug"
        ],
        "type": "string",
        "title": "Feedback Type"
      }
    }
  }

  arguments 52 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.

Served from the same domain, which is what was measured. Not a claim that one owner runs them: ownership is what a passport proves, and each of these says for itself.

• neumann.kromatic.com neumann mcp · 10 tools