medeval-mcp
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@medeval-mcpsearch clinical evidence for the new stent"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MedEval MCP (local)
Local-only Model Context Protocol gateway for the private MedEval medical-device regulatory workbench.
It lets an MCP client operate MedEval workspaces, canonicalized materials, evidence retrieval, CEP/CER generation and evaluation, workflow observability, and immutable document revisions. MedEval remains the system of record; this project is a thin, bounded adapter.
Safety boundary
stdio transport only; no network MCP listener
connects to loopback by default, with explicit opt-in for trusted private-network IPs
explicit workspace/task identifiers
allowlisted local upload roots
no delete, shell, deployment, or secret-management tools
asynchronous starts return task IDs and must be polled, not duplicated
product facts cannot be derived from external literature
document edits require the current
base_revision_id
See SECURITY.md.
Requirements
Windows or another Python 3.11+ environment
MedEval running at
http://127.0.0.1:8000Python package dependencies from
pyproject.toml
Install
cd C:\path\to\medeval-mcp
py -3.11 -m venv .venv
.\.venv\Scripts\python.exe -m pip install -e ".[test]"
Copy-Item .env.example .envThe MCP process reads normal environment variables. MCP clients generally supply them in their server configuration rather than loading .env automatically.
Configure
Minimum local configuration:
MEDEVAL_BASE_URL=http://127.0.0.1:8000
MEDEVAL_PROJECT_ROOT=C:\path\to\medeval
MEDEVAL_ALLOWED_FILE_ROOTS=C:\path\to\medeval;C:\path\to\materialsIf MedEval enables MEDEVAL_API_TOKEN, give this MCP process the same MEDEVAL_API_TOKEN; it is sent as X-API-Token. A signed browser/session token can instead be supplied as MEDEVAL_BEARER_TOKEN.
macOS client to a trusted LAN backend
When MedEval is listening on another computer in the same trusted LAN, use its literal private IP and opt in explicitly:
MEDEVAL_BASE_URL=http://192.168.0.166:8001
MEDEVAL_ALLOW_PRIVATE_NETWORK=true
MEDEVAL_PROJECT_ROOT=/Users/your-name/MedEval
MEDEVAL_ALLOWED_FILE_ROOTS=/Users/your-name/MedEval:/Users/your-name/DocumentsThe MCP remains a local stdio process on the Mac. Public IP addresses and domain names are still rejected.
Connect from Codex
Use examples/codex.mcp.json as the MCP server definition. The command must point to this project's .venv Python and use:
-m medeval_mcp.serverRestart Codex after changing the MCP configuration, then ask it to call medeval_health.
Run manually
MCP stdio uses standard output for protocol messages, so a manual run appears idle:
.\.venv\Scripts\python.exe -m medeval_mcp.serverUse an MCP client or Inspector to interact with it.
The bundled local launcher sets the loopback backend and upload roots before starting stdio:
.\scripts\run_local.ps1Protocol and backend smoke test:
.\.venv\Scripts\python.exe scripts\mcp_smoke.py --healthTool surface
The first release provides 21 tools:
workspace: health, project list, create/get workspace, workspace documents
observability: run list, run detail, bounded agent context
evidence: project documents, evidence search, section context
ingestion: allowlisted local material upload and canonicalization
generation: template list, start generation, generation/task status
evaluation: start evaluation
revisions: list, bounded read, diff, optimistic-lock patch
medeval_start_generation defaults to tag_index_agent, which uses MedEval's dependency-serial segmented writer. Full-context strategies remain opt-in.
Tests
.\.venv\Scripts\python.exe -m pytestThe tests use mock HTTP transports and do not start LLM generation or consume model quota. A separate integration smoke test lists MCP tools and calls the already-running local /api/health endpoint.
Not included yet
remote Streamable HTTP transport
xiaoyuu.medeploymentmulti-user API keys and workspace ownership
remote upload staging
destructive project/task deletion
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Maintenance
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