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Evals MCP Server

by cyanheadsversion 0.1.6i★ –iRuns on your computer
Registry nameio.github.cyanheads/evals-mcp-server

Install

Overview

Description from the maker (original English)

Author verifiable eval records through a draft→review→revise→submit loop with enforced graders.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • You fill in yourself: EVALS_DATA_DIR, EVALS_REQUIRE_CONFIRMATION, EVALS_DEFAULT_LICENSE, EVALS_CAPTURE_DIR, MCP_LOG_LEVEL

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "evals": {
      "command": "npx",
      "args": [
        "-y",
        "@cyanheads/evals-mcp-server"
      ],
      "env": {
        "EVALS_DATA_DIR": "your-value",
        "EVALS_REQUIRE_CONFIRMATION": "your-value",
        "EVALS_DEFAULT_LICENSE": "your-value",
        "EVALS_CAPTURE_DIR": "your-value",
        "MCP_LOG_LEVEL": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add evals --env EVALS_DATA_DIR=your-value --env EVALS_REQUIRE_CONFIRMATION=your-value --env EVALS_DEFAULT_LICENSE=your-value --env EVALS_CAPTURE_DIR=your-value --env MCP_LOG_LEVEL=your-value -- npx -y @cyanheads/evals-mcp-server

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "evals": {
      "command": "npx",
      "args": [
        "-y",
        "@cyanheads/evals-mcp-server"
      ],
      "env": {
        "EVALS_DATA_DIR": "your-value",
        "EVALS_REQUIRE_CONFIRMATION": "your-value",
        "EVALS_DEFAULT_LICENSE": "your-value",
        "EVALS_CAPTURE_DIR": "your-value",
        "MCP_LOG_LEVEL": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "evals": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@cyanheads/evals-mcp-server"
      ],
      "env": {
        "EVALS_DATA_DIR": "your-value",
        "EVALS_REQUIRE_CONFIRMATION": "your-value",
        "EVALS_DEFAULT_LICENSE": "your-value",
        "EVALS_CAPTURE_DIR": "your-value",
        "MCP_LOG_LEVEL": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

  • EVALS_DATA_DIR env
    Root folder for record JSON. The store manages drafts/, submitted/, and exports/ subdirs under it.
  • EVALS_REQUIRE_CONFIRMATION env
    When 'true', evals_submit_draft requests human confirmation before finalizing.
  • EVALS_DEFAULT_LICENSE env
    Default metadata.license applied when a draft omits one.
  • EVALS_CAPTURE_DIR env
    Directory of framework-written tool-call captures; when set, captures EvalsIDs resolve to full dumps.
  • MCP_LOG_LEVEL env
    Sets the minimum log level for output (e.g., 'debug', 'info', 'warn').

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account cyanheads, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

  • More stars than 0% of the other 18333 servers in this category
  • Published to the registry more recently than 64% of the other 18333 servers in this category
  • Basic checks equal to or better than 100% of the other 18333 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Evals MCP Server safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.6) reached the registry 25 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, Signoff

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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Runs on your computer★ 440MITUpdated 14 months ago
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Remote Desktop Commander

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Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Runs in the cloud★ 211Updated 2 days ago
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Signoff

by ayuanxx-max

Five gates that make an agent's 'done' provable: run them, read the verdict, audit the record.

Runs on your computerUpdated today
Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

@cyanheads/evals-mcp-server Author verifiable eval records through a draft → review → revise → submit loop with server-enforced graders; compile to JSONL/CSV/Inspect/lm-eval via MCP. STDIO or Streamable HTTP. 9 Tools • 1 Resource


Overview

Build verifiable eval records with server-enforced graders. Draft a record with its own executable grader, revise it field by field, and submit through a gate that requires the gold answer to pass, a negative case to fail, and an independent check to agree. Export to JSONL, CSV, Inspect AI, or lm-evaluation-harness.

Tools
ToolDescription
evals_describe_schemaReturn the required and optional fields plus grader options for a task type. Call before drafting.
evals_create_draftCreate a draft eval record carrying its own grader; returns the parsed record, a review protocol, and a verification subagent prompt.
evals_get_recordRead a draft or submitted record by id; the id is stable across submit.
evals_revise_draftApply a surgical set / append / unset patch to a draft by dotted path; re-runs the self-consistency check.
evals_discard_draftDelete a draft record by id. Draft-only.
evals_run_checkRun a grader spec against candidate answers and get PASS/REJECT per candidate, decoupled from any saved record.
evals_submit_draftFinalize a draft through the committability gate, then freeze it.
evals_list_recordsBrowse and filter records by status, domain, task type, or tag. Returns a compact summary per record.
evals_export_recordsCompile submitted records to JSONL, CSV, Inspect AI, or lm-evaluation-harness and write the artifact under exports/.
Resources
ResourceDescription
eval://record/{id}A single draft or submitted record by id — the same payload evals_get_record returns, for resource-capable clients.

All record data is also reachable through the tool surface — evals_get_record for a single record, evals_list_records to browse. The resource is a convenience mirror for clients that support resources, not the access path.

Capability reference

evals_describe_schema tool
  • Accepts task_type: numeric, exact_answer, set_answer, mcq, regex_answer, json_answer, or free_response.
  • Returns the gold shape, grader kinds, required/optional fields, and authoring notes from static schemas; mcq requires choices, and free_response requires llm_rubric.

evals_create_draft tool
  • Accepts a record with its grader and discrimination cases, plus optional verification and captures (EvalsIDs); mcq requires choices, and free_response requires llm_rubric.
  • Saves the record as a draft once its grader runs, and returns the normalized record, a review protocol, a verification-subagent prompt, and what submit still needs. A draft whose gold fails its grader is still saved.
  • Typed errors: grader_unexecutable, task_type_constraint, mcq_choice_mismatch.

evals_get_record tool
  • Reads a draft or submitted record by id, which stays stable across submit.
  • Returns the full grader, discrimination cases, and verification evidence; not_found points to evals_list_records.

evals_revise_draft tool
  • Applies set, append, and unset by dotted path to a draft; task_type and server-owned fields cannot be changed, and arrays are replaced whole or appended, not edited by index.
  • Re-validates the record and grader before writing, then returns the record plus changed entries (op, path, before, after). An unknown path rejects the whole patch.
  • Typed errors: not_found, record_frozen for a submitted id, invalid_patch_path, grader_unexecutable, task_type_constraint, mcq_choice_mismatch.

evals_discard_draft tool
  • Deletes a draft by draft_id and returns discarded: true.
  • A submitted record reports record_frozen; a missing or already discarded id reports not_found.

evals_run_check tool
  • Runs a grader against one or more candidates without a saved record; supply gold for exact_match, while target-embedding kinds such as numeric and mcq ignore it.
  • Returns PASS/REJECT, detail, and the resolved reference per candidate. llm_rubric can't be run here.
  • Numeric grading accepts only finite real values; unit-bearing, complex, nonfinite, and non-scalar candidates are rejected. units is documentation only.
  • Typed errors: grader_unexecutable, mcq_choice_mismatch.

evals_submit_draft tool
  • Finalizes by draft_id: gold must PASS, ≥1 negative must be REJECTED, and decorrelated verification must agree. Also checks captures against EVALS_CAPTURE_DIR, rejects duplicate content_hash, and can ask for confirmation via confirm or EVALS_REQUIRE_CONFIRMATION.
  • On success, freezes the record with submitted_at and checksum and returns status: submitted; a refusal leaves the draft intact. free_response records rely on verification alone and carry server_verified: false.
  • Typed errors: not_found, record_frozen, verification_incomplete, grader_failed_on_gold, verification_disagrees_with_gold, missing_negative_case, negative_case_passed, duplicate, decorrelation_violation, capture_unresolved, submit_declined.

evals_list_records tool
  • Filters by status (draft/submitted), domain, task_type, or tag; limit is a positive integer and defaults to 50.
  • Returns summaries (id, status, task_type, domain, tags, timestamps), newest-first, with shown, cap, totalCount, and truncated.

evals_export_records tool
  • Exports submitted records, optionally filtered by domain, task_type, or tag, as jsonl (lossless), csv (lossy summary), inspect (Inspect AI), or lm-eval (lm-evaluation-harness).
  • Writes under exports/ and returns the path, record count, byte size, and preview.

eval://record/{id} resource
  • Reads id from evals_list_records or a draft/submit response.
  • Returns the evals_get_record payload as application/json, or not_found when no record matches.

Features

Built on @cyanheads/mcp-ts-core: stdio and Streamable HTTP transports, pluggable auth (none / jwt / oauth), swappable storage (in-memory, filesystem, Supabase, Cloudflare KV/R2/D1), structured logging with optional OpenTelemetry tracing.

Eval authoring:

  • A draft → review → surgical-revise → submit loop, with the server both storing records and running each record's own grader to reject what doesn't hold up
  • Seven task types: numeric, exact_answer, set_answer, mcq, regex_answer, json_answer, free_response
  • A grader serialized with each record; deterministic kinds (numeric via math.js, exact_match, set_match, regex, mcq, json_match) run server-side, while llm_rubric relies on recorded independent verification
  • A submit gate: the gold must pass its own grader, ≥1 negative must be rejected, and a recorded decorrelated verification must agree with the gold
  • Plain JSON files under EVALS_DATA_DIR, with drafts, submitted records, and exports kept separate

Agent-friendly output:

  • evals_create_draft and evals_revise_draft return the parsed record, a per-field review protocol, and a ready-to-paste verification-subagent prompt
  • Draft and revise responses report pass/reject results for each positive and negative case
  • evals_list_records reports shown / cap / total count when the limit is hit
  • The submit gate fails with a typed reason plus a recovery hint

Getting started

Add the following to your MCP client configuration file. Set EVALS_DATA_DIR to a writable folder — the server manages drafts/, submitted/, and exports/ under it.

{

"mcpServers": { "evals-mcp-server": { "type": "stdio", "command": "bunx", "args": ["@cyanheads/evals-mcp-server@latest"], "env": { "MCP_TRANSPORT_TYPE": "stdio", "MCP_LOG_LEVEL": "info", "EVALS_DATA_DIR": "/absolute/path/to/evals-data" } } } }

Or with npx (no Bun required):

{

"mcpServers": { "evals-mcp-server": { "type": "stdio", "command": "npx", "args": ["-y", "@cyanheads/evals-mcp-server@latest"], "env": { "MCP_TRANSPORT_TYPE": "stdio", "MCP_LOG_LEVEL": "info", "EVALS_DATA_DIR": "/absolute/path/to/evals-data" } } } }

Or with Docker:

{

"mcpServers": { "evals-mcp-server": { "type": "stdio", "command": "docker", "args": [ "run", "-i", "--rm", "-e", "MCP_TRANSPORT_TYPE=stdio", "-v", "evals-data:/usr/src/app/evals-data", "ghcr.io/cyanheads/evals-mcp-server:latest" ] } } }

For Streamable HTTP, set the transport and start the server:

MCP_TRANSPORT_TYPE=http MCP_HTTP_PORT=3010 EVALS_DATA_DIR=./evals-data bun run start:http

Server listens at http://localhost:3010/mcp

Prerequisites
  • Bun v1.4.0 or higher (or Node.js v24+).
  • A writable directory for EVALS_DATA_DIR. No external API key is required.
Installation
  1. Clone the repository:
git clone https://github.com/cyanheads/evals-mcp-server.git
  1. Navigate into the directory:
cd evals-mcp-server
  1. Install dependencies:
bun install
  1. Configure environment:
cp .env.example .env

edit .env and set EVALS_DATA_DIR

Configuration

All server configuration is validated at startup via Zod schemas in src/config/server-config.ts.

VariableDescriptionDefault

| EVALS_DATA_DIR | Root folder for record JSON; the store manages drafts/, submitted/, and exports/ under

Only the beginning is shown; read the rest in the repo

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