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mitmproxy-mcp

CI Python 3.10+ License: MIT

MCP server for mitmproxy that lets any MCP client analyze, intercept, and replay HTTP/HTTPS traffic.

What is this

mitmproxy-mcp runs as a mitmproxy addon. It embeds an MCP server directly in the proxy process, giving AI agents access to 24 tools for traffic analysis, request replay, interception control, and proxy configuration.

All captured data stays in-memory. Sensitive values (tokens, passwords, API keys, JWTs) are automatically redacted before being sent to the AI.

Related MCP server: mitm-mcp

Installation

git clone https://github.com/moha-abdi/mitmproxy-mcp.git
cd mitmproxy-mcp

python3.10 -m venv .venv
source .venv/bin/activate

uv pip install -e ".[dev]"

# one-time: make mitmproxy/mitmdump/mitmweb use this env
# (prevents missing addon deps like `mcp` when system mitmproxy is used)
mitmproxy-mcp install-shims --force

Requires Python 3.10+ and mitmproxy >= 10.0.0.

Agent Skill (optional)

This repo also ships a skill definition in SKILL.md for the npx skills ecosystem.

Install it with:

npx skills add moha-abdi/mitmproxy-mcp

After installing, compatible coding agents can load the mitmproxy-mcp skill and get project-specific usage guidance.

Setup

1. Configure mitmproxy

Create or edit ~/.mitmproxy/config.yaml:

scripts:
  - /absolute/path/to/mitmproxy-mcp/addon.py

mcp_transport: sse
mcp_port: 9011

2. Start mitmproxy

mitmproxy      # interactive TUI
mitmweb        # web interface
mitmdump       # headless

The MCP server starts automatically on http://localhost:9011/sse. If the command still resolves to a system install, ensure your shim directory (default ~/.local/bin) is earlier in PATH, then restart the terminal.

3. Connect your AI client

All clients connect to the same SSE endpoint. Make sure mitmproxy is running before connecting.

OpenCode's local type bridges via supergateway. Requires Node.js.

Add to opencode.json in your project root, or ~/.config/opencode/opencode.json globally:

{
  "mcp": {
    "mitmproxy": {
      "type": "local",
      "command": ["npx", "-y", "supergateway", "--sse", "http://127.0.0.1:9011/sse"],
      "enabled": true
    }
  }
}

Via the CLI (project-level):

claude mcp add --transport sse mitmproxy http://localhost:9011/sse

To add globally across all projects:

claude mcp add --scope user --transport sse mitmproxy http://localhost:9011/sse

Or add manually to ~/.claude.json:

{
  "mcpServers": {
    "mitmproxy": {
      "type": "sse",
      "url": "http://localhost:9011/sse"
    }
  }
}

Add to .cursor/mcp.json in your project root:

{
  "mcpServers": {
    "mitmproxy": {
      "url": "http://localhost:9011/sse"
    }
  }
}

Add to ~/.codeium/windsurf/mcp_config.json:

{
  "mcpServers": {
    "mitmproxy": {
      "url": "http://localhost:9011/sse"
    }
  }
}

Add to .vscode/mcp.json in your project root:

{
  "servers": {
    "mitmproxy": {
      "type": "http",
      "url": "http://localhost:9011/sse"
    }
  }
}

Claude Desktop doesn't natively support SSE, so we use supergateway to bridge SSE to STDIO. Requires Node.js.

Add to your config (~/Library/Application Support/Claude/claude_desktop_config.json on macOS, %APPDATA%\Claude\claude_desktop_config.json on Windows):

{
  "mcpServers": {
    "mitmproxy": {
      "command": "npx",
      "args": ["-y", "supergateway", "--sse", "http://127.0.0.1:9011/sse"]
    }
  }
}

Any MCP client that supports SSE transport can connect directly to:

http://localhost:9011/sse

If your client only supports STDIO, use supergateway to bridge:

npx -y supergateway --sse http://127.0.0.1:9011/sse

Tools

Flow tools (12)

Tool

Description

get_flows

List captured flows with pagination and filtering

get_flow_by_id

Get complete flow details

search_flows

Search flows by regex pattern

get_flow_request

Get request details

get_flow_response

Get response details

mark_flow

Mark a flow (same behavior as UI mark action)

unmark_flow

Remove mark from a flow

focus_flow

Move UI focus to a visible flow by ID

focus_flow_index

Move UI focus by visible list index

clear_flows

Clear all captured flows (and UI view when sync includes clear)

get_flow_count

Count captured flows

export_flows

Export flows to HAR format

Replay tools (4)

Tool

Description

replay_request

Replay a captured request as-is

send_request

Send a new HTTP request

modify_and_send

Modify a captured request and send it

duplicate_flow

Clone a flow for comparison

Replay tool flows are reflected to mitmproxy's flow list when mcp_view_sync_actions includes replay (default all). replay_request replays the original flow in-place when replay sync is enabled; otherwise it creates a detached replay flow.

Intercept tools (5)

Tool

Description

set_intercept_filter

Set filter expression (e.g. ~u example.com)

get_intercepted_flows

List currently intercepted flows

resume_flow

Resume a single intercepted flow

resume_all

Resume all intercepted flows

drop_flow

Drop an intercepted flow

Config tools (3)

Tool

Description

get_options

Get current mitmproxy options

set_option

Set a mitmproxy option (dangerous ones are blocked)

get_status

Get proxy status and version info

Options

Pass via --set flag or set in ~/.mitmproxy/config.yaml:

Option

Default

Description

mcp_transport

stdio

Transport: stdio, sse, or tcp

mcp_port

9011

Port for SSE/TCP transport

mcp_max_flows

1000

Max flows to keep in memory (oldest evicted first)

mcp_redact

false

Redact sensitive data (tokens, keys, passwords) before sending to AI

mcp_redact_patterns

(empty)

Additional redaction patterns as JSON array (requires mcp_redact: true)

mcp_view_sync_actions

all

Which MCP actions sync to mitmproxy view: all, none, replay, clear, or replay,clear

Example:

mitmdump -s addon.py --set mcp_transport=sse --set mcp_port=9011 --set mcp_max_flows=5000

Privacy

By default, redaction is off -- you see the raw traffic as-is. To enable it, set mcp_redact to true in your config or via flags:

# ~/.mitmproxy/config.yaml
mcp_redact: true
# or via flags
mitmdump -s addon.py --set mcp_redact=true

When enabled, the following are automatically redacted before reaching the AI:

  • Bearer tokens, Basic auth credentials

  • API keys (header and query parameter)

  • Passwords, secrets

  • JWTs

  • Session IDs, auth tokens, session cookies

Request and response bodies are truncated to 10KB to prevent context overflow.

You can also add custom redaction patterns:

mitmdump -s addon.py --set mcp_redact=true --set mcp_redact_patterns='["internal_secret", "x-custom-key"]'

Project structure

mitmproxy-mcp/
  addon.py              thin wrapper for mitmproxy script loading
  mitmproxy_mcp/        main package
    __init__.py
    addon.py            mitmproxy addon with MCP server
    models.py           pydantic models for flow serialization
    storage.py          thread-safe in-memory flow storage
    privacy.py          redaction engine
    transport.py        stdio, sse, tcp transport layer
    tools/
      flows.py          flow query tools
      replay.py         replay and modification tools
      intercept.py      interception control tools
      config.py         proxy configuration tools
  tests/                test suite

Development

# install in editable mode (required for imports to work)
uv pip install -e ".[dev]"

# run tests
pytest tests/ -v

# run a specific test file
pytest tests/test_flow_tools.py -v

# with coverage
pytest tests/ --cov=mitmproxy_mcp --cov-report=html

# lint
ruff check .

# type check
mypy

License

MIT

A
license - permissive license
-
quality - not tested
F
maintenance

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