inti-brain

inti-brain

Connects AI assistants to Intigriti by syncing programs, scopes, and rules of engagement, then provides tools to search and generate actionable attack briefings.

Category
Visit Server

README

inti-brain

An MCP server that connects your AI assistant (Claude Code / Desktop, or any MCP client) to Intigriti. It pulls the programs you can access, their scopes (domains) and rules of engagement into a local SQLite database, then exposes tools to search programs, pull scope, and generate an actionable attack briefing via hack(handle).

It's the Intigriti equivalent of h1-brain.

Authorized testing only. Use this against programs you are permitted to test, and follow each program's scope and rules of engagement.

What it does

  • Syncs every Intigriti program you can access (handle, name, bounty range, status, industry).
  • Pulls each program's scope broken down by bounty tier, plus the rules of engagement — including the required request header (e.g. X-Intigriti-Username: {you}), safe-harbour status, and whether automated tooling is allowed.
  • hack(handle) returns a full briefing: bounty-eligible assets first, no-bounty assets, an explicit out-of-scope section, the required header, the ROE, and (optionally) weakness-pattern hits from a disclosed-report KB.

Requirements

Setup

git clone https://github.com/<you>/inti-brain.git
cd inti-brain
python3 -m venv venv
./venv/bin/pip install -r requirements.txt

cp .intienv.example .intienv   # then edit .intienv with your token

.intienv:

INTI_USERNAME=your_intigriti_username
INTI_API_TOKEN=your_researcher_api_token

Connect to Claude Code

claude mcp add inti-brain \
  -e INTI_USERNAME=your_username \
  -e INTI_API_TOKEN=your_token \
  -- /absolute/path/to/inti-brain/venv/bin/python \
     /absolute/path/to/inti-brain/server.py

For Claude Desktop, add an equivalent mcpServers entry pointing at venv/bin/python server.py with the two env vars.

First run

  1. fetch_programs — sync every program you can access.
  2. sync_all_scopes(bounty_only=True) — optional bulk scope pull for paying programs.
  3. hack(handle) — full attack briefing for one program (auto-pulls fresh scope).

Tools

Tool Description
fetch_programs() Sync all accessible programs into the DB
fetch_program_scope(handle) Fetch one program's domains + ROE
sync_all_scopes(bounty_only, limit) Bulk scope sync (one API call each — heavy)
search_programs(query, bounty_only, status, industry, min_max_bounty, limit) Search synced programs
search_scopes(program, asset, bounty_only, asset_type, limit) Search scope entries
get_program(handle) Full program detail incl. ROE + scope (auto-syncs)
hack(handle) Attack briefing: scope by bounty tier, required header, safe-harbour/tooling flags, out-of-scope section, ROE, KB hits
search_disclosed_reports(query, weakness, limit) Full-text pattern-KB search (needs optional KB, below)
get_disclosed_report(id) Full write-up from the pattern KB (needs optional KB)

Optional: weakness-pattern KB

The two *_disclosed_report* tools and the "Pattern KB hits" section of hack() read an optional SQLite corpus of public disclosed bug-bounty reports. Drop a disclosed_reports.db into this folder (the schema from h1-brain works as-is), or point DISCLOSED_DB_FILE at one. If absent, those tools degrade gracefully and the rest of the server works normally.

API

  • Base: https://api.intigriti.com/external/researcher/v1
  • Auth: Authorization: Bearer <researcher-api-token>
  • Programs: GET /programs?limit=&offset= (offset pagination)
  • Program detail / scope: GET /programs/{programId}

Notes

  • inti_data.db, .intienv, and disclosed_reports.db are git-ignored — your token and local data never get committed.
  • Always send the program's required header on in-scope requests, or you risk being flagged / out of scope.

License

MIT

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured