gitbook-mcp and GitIntel-MCP-Server

gitbook-mcp
51
Established
GitIntel-MCP-Server
44
Emerging
Maintenance 10/25
Adoption 12/25
Maturity 24/25
Community 5/25
Maintenance 13/25
Adoption 4/25
Maturity 11/25
Community 16/25
Stars: 19
Forks: 1
Downloads: 324
Commits (30d): 0
Language: JavaScript
License: MIT
Stars: 8
Forks: 6
Downloads: —
Commits (30d): 0
Language: TypeScript
License: MIT
No risk flags
No Package No Dependents

About gitbook-mcp

rickysullivan/gitbook-mcp

A Model Context Protocol (MCP) server that provides access to GitBook's API for AI assistants and LLM applications.

Exposes 12 content management tools (organization/space/collection discovery, full-text search, page retrieval in markdown or document formats) and 6 AI prompts for documentation workflows. Implements stdio transport for direct integration with Claude Desktop, VS Code Copilot, and JetBrains IDEs via standard MCP configuration. Supports optional organization and space filtering through CLI arguments or environment variables for scoped API access.

About GitIntel-MCP-Server

hoangsonww/GitIntel-MCP-Server

A Git intelligence MCP server built with Node.js and TypeScript that analyzes local Git repositories to surface insights like hotspots, churn, temporal coupling, knowledge maps, and risk scoring. Designed for AI agents, it exposes repository analytics tools through the Model Context Protocol (MCP) while keeping all data local and read-only.

Exposes 12 specialized analysis tools (hotspots, temporal coupling, knowledge maps, churn, complexity trends, risk scoring) that transform raw git output through multi-stage pipelines into scored, formatted tables and actionable insights. Built on stdio JSON-RPC transport with safe subprocess execution via `execFile`, it auto-detects repositories from working directory or accepts explicit paths, and ships with pre-computed resources (repository summary, activity feeds) for quick snapshot access. Designed for local-first deployment across Claude Code, Codex, and other MCP clients—includes Docker multi-stage builds, Kubernetes Kustomize manifests, and Terraform/CloudFormation templates for containerized or cloud-native environments.

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