Borrowing it
Nothing to install: this file belongs to BjornMelin/qdrant-neo4j-crawl4ai-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/BjornMelin/qdrant-neo4j-crawl4ai-mcp/main/CLAUDE.mdgit clone --depth 1 https://github.com/BjornMelin/qdrant-neo4j-crawl4ai-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/bjornmelin/qdrant-neo4j-crawl4ai-mcp/claude-md)<a href="https://agentmods.dev/instructions/bjornmelin/qdrant-neo4j-crawl4ai-mcp/claude-md"><img src="https://agentmods.dev/badge/instructions/bjornmelin/qdrant-neo4j-crawl4ai-mcp/claude-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/bjornmelin/qdrant-neo4j-crawl4ai-mcp/claude-md"><img src="https://agentmods.dev/badge/instructions/bjornmelin/qdrant-neo4j-crawl4ai-mcp/claude-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.02613 | $0.02613 |
| Opus 5 | $0.01307 | $0.01307 |
| Sonnet 5 | $0.00523 | $0.00523 |
| Haiku 4.5 | $0.00261 | $0.00261 |
Grade A, and why
qdrant-neo4j-crawl4ai-mcp CLAUDE.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 303 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
Project Overview
This is an Agentic RAG MCP Server that combines vector search (Qdrant), knowledge graphs (Neo4j), and web intelligence (Crawl4AI) through a unified Model Context Protocol (MCP) interface. The system provides autonomous query routing and result fusion using FastMCP 2.0.
Key Architecture
- FastMCP 2.0: Service composition pattern with mounted endpoints
- Async-First: All operations use async/await for high concurrency
- Service Layer: Three main services (Vector, Graph, Web) with unified interfaces
- MCP Tools: Individual tool registrations for each service type
- Production-Ready: JWT auth, rate limiting, monitoring, security headers
Build System & Dependencies
Primary Tools
- uv: Package management (replaces pip) - use
uv syncfor installation - ruff: Code formatting and linting - run
ruff check . --fixthenruff format . - mypy: Type checking - run
mypy . - pytest: Testing framework with async support
Development Commands
# Install dependencies
uv sync
# Install with dev dependencies
uv sync --dev
# Run the server locally
uv run python -m qdrant_neo4j_crawl4ai_mcp
# Run with Docker
docker-compose up -d
# Run tests
uv run pytest
# Run tests with coverage
uv run pytest --cov=qdrant_neo4j_crawl4ai_mcp --cov-report=html
# Run specific test suites
uv run pytest tests/unit/
uv run pytest tests/integration/
uv run pytest tests/security/
# Code quality checks
uv run ruff check . --fix
uv run ruff format .
uv run mypy .
# Security scanning
uv run bandit -r src/
Test Execution
- Unit tests:
tests/unit/- Fast, isolated component tests - Integration tests:
tests/integration/- Service integration tests - Security tests:
tests/security/- Authentication and authorization tests - Performance tests:
tests/performance/- Load and benchmark tests - Property tests:
tests/property/- MCP protocol compliance tests
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 303 lines · 2,613 tokens per session scan A 17f052784233
qdrant-neo4j-crawl4ai-mcp CLAUDE.md is an instructions file published in the GitHub repository BjornMelin/qdrant-neo4j-crawl4ai-mcp (7 stars, last pushed 1y ago), licensed MIT. It adds 2,613 tokens to every session, about $0.0131 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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