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Fiddler-MCP-Server

Provides agent chat for analysing Fiddler traffic using LLM models through MCP server and custom tools with robust python harness.

Install / Use

claude mcp add lucas-link-code -- npx -y github:lucas-link-code/Fiddler-MCP-Server

If the server publishes to npm under a different name, use that package instead — check the repo README.

About this skill
šŸ”Œ

MCP Server

Model Context Protocol server

Quality Score

81/100

Category

Security

Supported Platforms

Claude Code
Claude Desktop

Our assessment of Fiddler-MCP-Server

Fiddler-MCP-Server scores 81/100 on our quality scale, 997th of 1,111 Security skills we index.

Its MCP Server is 7.3 KB long, well organised into 11 sections with 3 code examples: a thorough specification that gives an agent plenty to work with.

It has 10 GitHub stars, so there is little community track record yet; judge it on its content.

Substance
29/30
Structure
18/20
Description
15/15
Adoption
4/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 33 days ago, so Fiddler-MCP-Server is actively maintained.
  • No license is declared. By default that means all rights are reserved: you can read it, but reusing or redistributing it is not clearly permitted. Ask the author before building on it commercially.
  • Its trust signals score 85/100, with 1 caution from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.

Automated pattern scan on 2026-10-15. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

Fiddler-MCP-Server compared with similar skills

All 4 of these similar skills score higher than Fiddler-MCP-Server; compare them before choosing.

SkillScoreStarsUpdatedFormat
Fiddler-MCP-Server (this skill)by lucas-link-code811033d agoMCP Server
Agent-Reachby Panniantong10097.3k6d agoCLAUDE.md
headroomby headroomlabs-ai10075.4k1d agoCLAUDE.md
CowAgentby zhayujie10047.4ktodayCLAUDE.md
Scraplingby D4Vinci10087.6ktodayMCP Server

Frequently asked questions

How do I install Fiddler-MCP-Server?
Run claude mcp add lucas-link-code -- npx -y github:lucas-link-code/Fiddler-MCP-Server. The install tabs above show the steps for each supported agent.
Which AI agents does Fiddler-MCP-Server work with?
It is written for Claude Code and Claude Desktop, as a MCP Server file. Other agents that read the same format can often use it too.
Is Fiddler-MCP-Server safe to use?
Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It declares no license and scores 85/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is Fiddler-MCP-Server still maintained?
The repository was last updated 33 days ago, so Fiddler-MCP-Server is actively maintained.

Fiddler MCP Server

Created a GenAI assisted workflow that helps analysts examine HTTP traffic captured in Fiddler. Analysts can ask questions in natural language about redirects, scripts, downloads, headers and suspicious behaviour instead of reviewing each web session manually.

Implemented an MCP bridge as the interface between Fiddler and LLM clients, with support for Gemini, DeepSeek and OpenRouter. Developed 10 analysis tools which let the model search sessions, inspect headers and bodies, compare traffic, build timelines and review EKFiddle findings.

Built an agentic analysis workflow which triggers tools on demand to deliver comprehensive malicious website analysis in a report. The analyst can see the raw evidence behind each answer and remains responsible for the final decision.

Quick Start

Windows analysis VM with Fiddler Classic and Python 3.10 or later.

  1. Download these two files from the repo root into the same folder:
    • Fiddler-MCP-Setup.bat
    • Fiddler-MCP-Bundle.zip
  2. Double-click Fiddler-MCP-Setup.bat
  3. Setup extracts to %USERPROFILE%\Fiddler_MCP, installs dependencies, deploys CustomRules.js, and starts the bridge plus client
  4. API keys are not required during setup. Enter them in the client window when prompted
  5. In Fiddler: Rules > Reload Script (Ctrl+R)

Day-to-day restart from the install folder:

start-fiddler-mcp.bat

5ire-bridge.py runs inside the client as the MCP child. There is no third console window.

Guides: QUICK_START_GUIDE.txt, Fiddler_MCP_Guide.pdf

Architecture

Fiddler Classic          enhanced-bridge.py        5ire-bridge.py         gemini-fiddler-client.py
     |                         |                        |                      |
     |   POST /live-session    |                        |                      |
     |------------------------>|  REST API (8081)       |                      |
     |   (JSON session data)   |----------------------->|   MCP tools/list     |
     |                         |  /api/sessions/...     |   tools/call         |
     |                         |                        |--------------------->|
     |                         |                        |   stdin/stdout MCP   |
     |                         |                        |                      |
     |                         |                        |   Native tool loop
     |                         |                        |---------------------> LLM API
  1. Fiddler captures traffic and POSTs JSON via CustomRules.js
  2. enhanced-bridge.py buffers sessions and exposes REST on port 8081
  3. 5ire-bridge.py exposes MCP tools that call that REST API
  4. gemini-fiddler-client.py binds those tools on the active LLM provider, runs the chat loop, and executes every tool through call_tool

The model never talks to Fiddler or Python directly. The client is the middleman.

MCP Tools

| Tool | Purpose | | -------------------------------- | ------------------------------------------------------ | | fiddler_mcp__live_sessions | List recent sessions with metadata and risk indicators | | fiddler_mcp__sessions_search | Filter by host, URL, status, method, size, MIME type | | fiddler_mcp__session_headers | Get request/response headers for a session | | fiddler_mcp__session_body | Get request/response bodies | | fiddler_mcp__compare_sessions | Fetch several session bodies for side-by-side analysis | | fiddler_mcp__live_stats | Buffer depth, capture rate, uptime | | fiddler_mcp__sessions_timeline | Aggregate by time, host, status, or content type | | fiddler_mcp__sessions_clear | Clear buffers after exporting evidence | | fiddler_mcp__ekfiddle_sessions | List sessions already flagged by EKFiddle | | fiddler_mcp__ekfiddle_threats | High-risk EKFiddle hits for triage |

Tools return raw data. The LLM reasons over headers, bodies, and EKFiddle comments.

Slash commands in the client: /investigate, /investigate <host>, /clear, /clearchat, /model, /stats, /tools, /help, /quit.

Repository layout

ā”œā”€ā”€ Fiddler-MCP-Setup.bat        # Outer installer (place next to the zip)
ā”œā”€ā”€ Fiddler-MCP-Bundle.zip       # Runtime package
ā”œā”€ā”€ pack-release.bat             # Rebuild the zip from package/
ā”œā”€ā”€ package/                     # Files inside the zip, plus tests
└── docs/                        # Operator guides and PDFs

Source for a rebuild lives in package/. Maintainer: run pack-release.bat from the repo root.

Documentation

LLM providers

Gemini is the default. DeepSeek and OpenRouter are optional. Switching providers uses /model in the client. A missing key is prompted once and saved locally in gemini-fiddler-config.json, which is not in this repository.

OpenRouter accepts a freeform vendor/model id when an OpenRouter key is present. Curated /model numbers for OpenRouter are 14 to 18. Direct DeepSeek API remains /model 12 and /model 13.

A same host OpenAI compatible server can reuse the DeepSeek slot by pointing deepseek_base_url at localhost. No extra provider exists in this repo. Steps: LOCAL_MODEL.md.

Prerequisites

  • Windows 10/11 analysis VM, or macOS/Linux for development
  • Python 3.10 or later
  • Fiddler Classic, run at least once so Scripts exists
  • At least one LLM API key when the client starts: Gemini, DeepSeek, or OpenRouter

Troubleshooting

If dependency install fails, run package/install-dependencies-manual.bat then package/deploy-mcp.bat.

On FLARE VMs, pip often fails with CERTIFICATE_VERIFY_FAILED talking to pypi.org even when curl/ping work. pip uses its own CA bundle; Windows urllib can still succeed. pypi_tls.py probes pip's stack and retries with --trusted-host on cert failure. Force lab mode with set FIDDLER_PIP_TRUSTED_HOST=1.

mcp 2.0 removed FastMCP. The bundle pins mcp>=1.0.0,<2.0.0. If 5ire-bridge fails with No module named mcp.server.fastmcp, reinstall that pin.

FLARE SSL_CERT_FILE pointing at a single lab root such as C:\ProgramData\Rep\rootCA.crt must not be the only CA store for DeepSeek. The client merges it with the OS store and certifi. You should not need DEEPSEEK_SSL_VERIFY=0 after this.

See TROUBLESHOOTING.txt. Common issues: Fiddler must be closed when CustomRules.js is copied; port 8081 must be free; Rules > Reload Script after deploy.

Use cases

  • Malware traffic analysis
  • EKFiddle CustomRegex drafting from live session bodies
  • Session forensics and timeline reconstruction
  • JavaScript and redirect-chain review

Acknowledgments

  • EKFiddle for rule format inspiration
  • Model Context Protocol specification
  • Fiddler community

Related Skills

View on GitHub
GitHub Stars10
CategorySecurity
Updated1mo ago
Forks5

Languages

Python

Trust signals

85/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

1 medium1 info
Fiddler-MCP-Server — MCP Server: Install & Safety Check | SkillAgent