API Debugger 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., "@API Debugger MCPCompare the /users endpoint response between staging and production for regressions"
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.
API Debugger MCP š
A production-oriented Model Context Protocol (MCP) server for inspecting, testing, validating, comparing, and debugging HTTP APIs with FastMCP.
Why this project?
API failures often require jumping between API clients, OpenAPI documentation, logs, test suites, and bug trackers. API Debugger MCP gives an MCP-compatible AI agent a structured toolkit for performing those investigations.
Related MCP server: mcp-api-tools
Features
12 MCP tools for API debugging and QA
Safe secret redaction for common credential fields and headers
Configurable timeout and response-size limits
Private/local network blocking by default
JSON-schema-style response contract validation
Regression comparison between response bodies
Multi-endpoint health checks
Automated API test scenario generation
Structured bug-report generation
End-to-end incident investigation workflow
MCP resource and reusable prompt
Docker support
Pytest + coverage
Ruff linting
GitHub Actions CI across Python 3.10ā3.12
MCP tools
inspect_endpointsend_requestvalidate_responsecompare_responsesanalyze_errordetect_api_issuegenerate_api_testsgenerate_bug_reportcheck_contractapi_health_checkredact_sensitive_datainvestigate_incident
Project structure
api-debugger-mcp/
āāā .github/workflows/ci.yml
āāā docs/
āāā src/api_debugger_mcp/
ā āāā analysis.py
ā āāā client.py
ā āāā config.py
ā āāā models.py
ā āāā security.py
ā āāā server.py
ā āāā tools.py
āāā tests/
āāā .dockerignore
āāā .env.example
āāā .gitignore
āāā Dockerfile
āāā LICENSE
āāā Makefile
āāā docker-compose.yml
āāā pyproject.tomlQuick start
1. Create a virtual environment
python -m venv .venvWindows:
.venv\Scripts\activatemacOS/Linux:
source .venv/bin/activate2. Install
pip install -e ".[dev]"3. Configure
Copy .env.example to .env and set only the values required for your environment.
Never commit real API keys or bearer tokens.
4. Run locally
For an HTTP MCP server:
api-debugger-mcpThe default MCP endpoint is:
http://localhost:8000/mcpFor local stdio mode:
MCP_TRANSPORT=stdiothen run:
api-debugger-mcpDocker
docker compose up --buildThe server is exposed on port 8000.
Testing
pytestLint:
ruff check .Format:
ruff format .Example MCP workflow
An MCP-compatible agent can combine the tools like this:
investigate_incident
ā
inspect_endpoint
ā
send_request
ā
detect_api_issue
ā
analyze_error
ā
check_contract
ā
generate_bug_reportFor regression testing:
send_request (baseline)
ā
send_request (current)
ā
compare_responses
ā
validate_responseSecurity notes
This server is designed to avoid accidental credential leakage and unsafe network access by default.
Common auth/cookie/API-key headers are redacted from returned results.
Common secret fields are redacted recursively.
Requests to local/private IP targets are disabled by default.
Do not commit
.envwith real credentials.In production, place the MCP server behind your organization's authentication and network controls.
Add an explicit allowlist before enabling private-network requests in sensitive environments.
Production roadmap
OpenAPI 3.x import and endpoint discovery
OAuth/API-key secret providers
Persistent regression baselines
Sentry/observability integration
Jira/GitHub issue creation
Request correlation IDs
Rate limiting
Audit logging
RBAC/authentication
Async parallel health checks
MCP task/background execution for long-running investigations
License
MIT
This server cannot be installed
Maintenance
Resources
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Looking for Admin?
If you are the server author, to access and configure the admin panel.
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