ErrorLens MCP
Provides structured error recovery and classification for the GitHub MCP server, acting as a proxy to prevent blind duplicate writes and provide retry guidance.
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., "@ErrorLens MCPclassify the timeout error from the write call"
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.
ErrorLens MCP
Structured error recovery for MCP agents.
MCP servers often fail with vague messages. ErrorLens turns those failures into structured, retry-aware, state-aware guidance that agents can use.
Why Use It
When an MCP tool call fails, agents need to know more than "something went wrong." They need to know whether retrying is safe, whether a write may have partially happened, what evidence matters, and what recovery step should come next.
ErrorLens MCP is built for that pressure point:
Prevents blind duplicate writes after ambiguous timeouts.
Converts opaque upstream failures into stable machine-readable categories.
Keeps recovery guidance compact enough for agent context windows.
Preserves successful upstream MCP responses while wrapping failures with structured
isError: truepayloads.Stores privacy-preserving local JSONL traces for replay and reports.
Runs locally with no telemetry, no model dependency, and no API key.
Related MCP server: error2fix
What It Does
Classifies opaque MCP and tool failures into a compact structured error model.
Tells agents whether retrying is safe, whether state may have changed, and what to do next.
Exposes a companion MCP server for diagnostics.
Runs as an MCP proxy for local stdio and remote Streamable HTTP upstream servers.
Records local JSONL traces with redaction enabled by default.
Keeps trace data in a per-session OS temp directory and cleans it up on graceful server shutdown.
Ships a CLI for init, doctor, traces, replay, report, proxy, and adapter rule tests.
ErrorLens is a reliability layer, not a security sandbox. It does not send traces to a cloud service and it has no model or API-key dependency.
Requirements
Node.js 22.12.0 or newer
npm
Windows, Linux, or macOS
Install
Install from npm:
npm install -g mcp-errorlens
errorlens --helpOr run it without a global install:
npx mcp-errorlens --helpInstall the tagged GitHub release from source:
git clone --branch v0.1.0 https://github.com/Master0fFate/ErrorLens-MCP.git
cd ErrorLens-MCP
npm install
npm run build
npm run verifyRun the CLI from source:
node dist/cli/index.js --helpOr link it locally while developing:
npm link
errorlens --helpThe compiled package uses portable Node APIs and is designed to work on Windows, Linux, and macOS.
Companion MCP Server
For a global npm install:
{
"mcpServers": {
"errorlens": {
"command": "errorlens-companion",
"args": []
}
}
}For npx without a global install:
{
"mcpServers": {
"errorlens": {
"command": "npx",
"args": ["-y", "--package", "mcp-errorlens", "errorlens-companion"]
}
}
}Tools:
classify_errorrecommend_recoveryreplay_tracesummarize_failuresgenerate_adapter_rulerules_test
Proxy Mode
Create a local config:
errorlens init --dir .errorlensEdit .errorlens/config.yaml, then run:
errorlens proxy --config .errorlens/config.yamlErrorLens lists upstream tools and forwards calls over stdio or Streamable HTTP.
Tool execution failures are returned as normal MCP tool results with isError: true,
machine-readable structuredContent, and a structured ErrorLens JSON payload.
Successful tool responses are preserved. Unknown exposed tools remain protocol errors,
as required by MCP.
Runtime trace files are session-scoped and live under the operating system's temp
directory; the proxy and companion server do not write trace data into the working
directory. errorlens init only creates the user-requested configuration directory.
Relative trace and adapter-rule paths are resolved against the config file. Adapter rules can be loaded globally or per upstream server:
rules:
custom_paths: []
servers:
github:
transport: streamable_http
url: https://example.com/mcp
headers:
Authorization: ${GITHUB_AUTH_HEADER}
adapter_rules:
- rules/github.yamlCLI Commands
errorlens init --dir .errorlens
errorlens doctor --config .errorlens/config.yaml
errorlens report --trace .errorlens/traces.jsonl
errorlens replay --trace .errorlens/traces.jsonl
errorlens traces --trace .errorlens/traces.jsonl
errorlens rules test --file ./rules/github.yaml
errorlens proxy --config .errorlens/config.yamlDemo
The repo includes a fake broken MCP server used by the QA smoke tests:
npm run verify
node dist/qa/companion-smoke.js rate-limit
node dist/qa/proxy-smoke.js write-timeout
node dist/qa/proxy-smoke.js adapter-ruleThe proxy demo shows a write-like timeout classified as SIDE_EFFECT_UNKNOWN
with retry.safe=false, which prevents blind duplicate writes.
Privacy
No telemetry.
Local trace files only.
Redaction enabled by default.
Environment variable values are never printed by
doctor.ErrorLens improves recovery semantics; it does not provide formal security isolation.
Development
npm run lint
npm run build
npm test
npm run verifyThe CI workflow runs the verification suite across Windows, Linux, and macOS.
This server cannot be installed
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Latest Blog Posts
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/Master0fFate/ErrorLens-MCP'
If you have feedback or need assistance with the MCP directory API, please join our Discord server