Mmcp.market

Fermi MCP server

online · 100% uptime
by Kromatic-Innovation·io.github.Kromatic-Innovation/fermi·v1.0.0
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Calibrated probability distributions from natural-language questions via REST and MCP.

C55/100grade C
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Safety scan
C55/100

full report

Adoption
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If you have run it, two minutes of your experience saves the next person an afternoon.

Fermi tools (3, 2 write)

write = sends, deletes, buys or posts
  • buy_creditswrite actionFree

    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: ValueError: if authentication fails, no payment method is on file, or the card is declined.

  • estimateFree

    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: ValueError: if the estimate service rejects the request (bad tier, out of credits, unknown provider, missing disclaimer acknowledgement).

  • feedbackwrite actionFree

    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: ValueError: if validation fails or email delivery fails.

Public scan report

scanner v0.1.9 · 2026-09-27 · same rubric, same numbers if you re-run it

1 high1 low
  • –Code scanremote-only server, no package to scann/a
  • Live reliabilityremote reachable in 451ms20/20
  • Tool poisoning3 tool descriptions checked13/15
  • Auth qualityopen endpoint exposes 2 write-action tools with no auth3/15
  • Maintenancerepository not readable: repo not found3/15
  • Maintainer identityno repository or website to verify2/10

Findings (2)

  • highWrite-action tools reachable without authenticationauth.open-write
  • lowUnusually long tool description (over 2,000 characters)poison.long-description
    tool estimate: …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: ValueError: if the estimate service rejects the request (bad tier, out of credits, unknown provider, missing disclaimer acknowledgement). …
Overall 55/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

Install Fermi in Claude Code, Cursor or VS Code

claude mcp add --transport http fermi https://fermi.krobar.ai/mcp/sse/
Add to Cursor

Fermi: common questions

Is Fermi MCP server safe?
With care: it is graded C, so read the findings first (55/100). Read the Fermi safety report
How do I install Fermi?
It runs remotely at fermi.krobar.ai. Add it to Claude Code, Cursor, VS Code or Claude Desktop with the snippets above, or call it through the mcp.market gateway without installing anything.
Does Fermi need an API key?
Not as far as the registry entry and our scan can tell: no credentials are declared or required.
Is Fermi maintained?
The latest release is v1.0.0.
Is Fermi up?
100% of our last 28 checks got an answer. We check remote servers about four times a day.
What can I use instead of Fermi?
Servers from other publishers that do the same job: Ask Jev MCP server.

Alternatives to Fermi

Same job from other publishers: the closest match first, then the best rated.

  • Ask Jev
    Evaluate state with typed choice, score, and probability questions.
    A

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