
Perf Mcp
io.github.Perf-AIPublished by GitHub account Perf-AIv0.1.1Updated Nov 10, 2026
Fact-check and fix AI outputs. Hallucination detection, schema validation, auto-repair.
Overview
Fact-checks and repairs AI-generated output: detects hallucinations, validates and fixes JSON against a schema, and routes chat requests to a chosen model.
- What you can do
- Verify LLM-generated text and get corrected claims with confidence scores
- Validate generated JSON against a schema and auto-repair type, enum and missing-field errors
- Correct general output by classifying the error type (hallucination, schema violation, inconsistency, instruction drift)
- Route chat requests to one of 20+ models in an OpenAI-compatible format
- When to use it
- Useful when assistant output is shown to users or fed into downstream systems and you want a second check for factual errors or malformed JSON before it lands. Also relevant if you want one endpoint that picks a model per request.
- Requirements
- Runs locally via npx, so Node.js is needed. Requires a Perf API key in the PERF_API_KEY environment variable; an optional PERF_BASE_URL overrides the API endpoint. Network access to the Perf service is required.
Installation
In SourceWeft
- Open Perf Mcp in the dashboard and add it to a workspace.
- Enable the server for the chats that should use its tools.
Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.
Other MCP clients
Follow the launch instructions in the repository.
README
perf-mcp
Fact-check and fix AI outputs. Catches hallucinations, repairs broken JSON, corrects errors — before they reach users.
Works with Claude Code, Cursor, Windsurf, Cline, and any MCP-compatible client.
Quick Start
Add to your MCP client config:
Get your API key at dashboard.withperf.pro — 200 free verifications, no credit card.
Tools
perf_verify
Detect and repair hallucinations in LLM-generated text. Uses multi-channel verification (web search, NLI models, cross-reference) — not just another LLM check.
perf_validate
Validate LLM-generated JSON against a schema and auto-repair violations. Fixes malformed enums, wrong types, missing fields, hallucinated properties.
perf_correct
General-purpose output correction. Classifies the error type and applies the right fix — hallucination, schema violation, semantic inconsistency, or instruction drift.
perf_chat
Route LLM requests to the optimal model automatically. Selects between GPT-4o, Claude, Gemini, and 20+ models based on task complexity. OpenAI-compatible format.
Setup by Client
Claude Code
Add to your project's .mcp.json:
Cursor
Settings → MCP → Add Server:
Windsurf
Add to ~/.codeium/windsurf/mcp_config.json:
Environment Variables
Pricing
1 tool call = 1 credit. Get started at dashboard.withperf.pro.
License
MIT
Source: README.md at commit e0e678a
Tools
0Version history
1- v0.1.1LatestSep 16, 2026
Score
50% of the applicable checks met
How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.
- Reached in the last 30 days25 pts
Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.
- Auth declared10 pts
Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.
- Tools listed15 pts
Answer tools/list without a credential, or ship a package that starts in a sandbox without one.
- DescriptionRequired15 pts
- Logo10 pts
- Documentation15 pts
- License10 pts