Docs MCP Server (Grounded Docs) - Local Documentation Index for AI Assistants
Research Date: January 26, 2026 Source URL: https://grounded.tools GitHub Repository: https://github.com/arabold/docs-mcp-server npm Package: https://www.npmjs.com/package/@arabold/docs-mcp-server Version at Research: v1.36.0 License: MIT
Overview
Docs MCP Server (branded as "Grounded Docs") is an open-source MCP server that solves AI hallucinations and outdated knowledge by providing a personal, always-current documentation index. It fetches official docs from websites, GitHub, npm, PyPI, and local files, allowing AI assistants to query the exact library versions being used in a project.
Core Value Proposition: Open-source alternative to Context7, Nia, and Ref.Tools that runs entirely on your machine with full privacy.
Problem Addressed
| Problem | How Docs MCP Server Solves It |
|---|---|
| AI models have outdated training data | Fetches documentation directly from official sources on demand |
| AI hallucinations about APIs and features | Grounds LLMs in real, current documentation |
| Context window limitations for large docs | Semantic vector search retrieves only relevant chunks |
| Version mismatches (AI knows v1, user has v3) | Version-specific queries target exact library versions in project |
| Privacy concerns with cloud services | Runs entirely on local machine; code never leaves your network |
| Single-format documentation sources | Processes HTML, Markdown, PDF, Word, Excel, PowerPoint, and source code |
Key Statistics (as of January 26, 2026)
| Metric | Value |
|---|---|
| GitHub Stars | 954 |
| Forks | 113 |
| Contributors | 8 |
| Open Issues | 33 |
| Primary Language | TypeScript (99%) |
| npm Package | @arabold/docs-mcp-server |
| Latest Version | v1.36.0 (Jan 15, 2026) |
| Created | March 17, 2025 |
Key Features
1. Multi-Source Documentation Indexing
- Web Scraping: Index any documentation website using Playwright
- GitHub Repositories: Index README, docs folders, source code
- Package Registries: Fetch from npm and PyPI
- Local Files: Index local folders and zip archives
- llms.txt Support: Automatic detection of LLM-ready documentation files
2. Rich File Format Support
- HTML and Markdown
- PDF documents
- Microsoft Office (Word .docx, Excel, PowerPoint)
- Source code files
- Password-protected PDFs
3. Semantic Vector Search
- Multiple Embedding Providers: OpenAI, Ollama, Google Gemini, Azure, AWS
- Hybrid Search: Combines vector similarity and full-text search
- Reciprocal Rank Fusion (RRF): Configurable weights for optimal ranking
- Dual-Mode FTS: Exact phrase and keyword matching for improved recall
4. Version-Specific Queries
- Index multiple versions of the same library
- Query targets exact version in use
- Version tracking with re-indexing capability
- Change detection for documentation updates
5. Privacy-First Architecture
- Runs entirely on local machine
- No code or queries sent to external servers
- SQLite database with schema migrations
- Optional telemetry (privacy-first design)
6. Multiple Access Interfaces
- Web UI: Add/manage documentation at http://localhost:6280
- CLI: Command-line management
- MCP Protocol: Integration with Claude, Cline, Roo, etc.
- SSE Endpoint: Server-Sent Events for real-time updates
Technical Architecture
Documentation Sources
|
v
+---------------------------+
| Scraper Strategies |
| - Web (Playwright) |
| - Local filesystem |
| - Package registries |
+---------------------------+
|
v
+---------------------------+
| Content Fetchers |
| - HTTP |
| - Filesystem |
| - Registry APIs |
+---------------------------+
|
v
+---------------------------+
| Processing Pipelines |
| - Middleware chains |
| - Content-type handling |
+---------------------------+
|
v
+---------------------------+
| Document Splitters |
| - SemanticMarkdown |
| - JsonDocument |
| - TextDocument |
| - GreedySplitter (size) |
+---------------------------+
|
v
+---------------------------+
| Embedding Generation |
| - OpenAI, Gemini |
| - Ollama (local) |
| - Azure, AWS |
+---------------------------+
|
v
+---------------------------+
| SQLite Storage |
| - libraries table |
| - versions table |
| - documents table |
+---------------------------+
|
v
+---------------------------+
| Hybrid Search |
| - Vector similarity |
| - Full-text search |
| - RRF ranking |
+---------------------------+
Deployment Modes
Unified Mode (Default):
- Single process with MCP server, web interface, embedded worker
- Suitable for development and simple deployments
- Direct method calls between components
- Local event propagation via EventBus
Distributed Mode (Docker Compose):
- Separate coordinator and worker processes
- Hub (shared worker) + Spokes (Web, MCP, CLI)
- tRPC for inter-process communication
- WebSocket for real-time events
- Scalable processing across containers
Protocol Auto-Detection
- No TTY: stdio transport for direct MCP communication
- Has TTY: HTTP transport with Server-Sent Events
- Manual override:
--protocol stdio|http
Installation and Usage
Quick Start
# Start server (requires Node.js 20+)
npx @arabold/docs-mcp-server@latest
# Open Web UI
# http://localhost:6280
# Add to MCP client config
{
"mcpServers": {
"docs-mcp-server": {
"type": "sse",
"url": "http://localhost:6280/sse"
}
}
}
Docker Deployment
docker run --rm \
-v docs-mcp-data:/data \
-v docs-mcp-config:/config \
-p 6280:6280 \
ghcr.io/arabold/docs-mcp-server:latest \
--protocol http --host 0.0.0.0 --port 6280
Enable Embeddings (Recommended)
# OpenAI
OPENAI_API_KEY="sk-proj-..." npx @arabold/docs-mcp-server@latest
# Or Ollama (local, free)
OLLAMA_BASE_URL="http://localhost:11434" npx @arabold/docs-mcp-server@latest
MCP Tools Provided
The server exposes tools via MCP protocol:
| Tool | Description |
|---|---|
scrape_docs |
Index documentation from URL or local path |
search_docs |
Semantic search across indexed content |
list_libraries |
Show all indexed libraries |
list_versions |
Show versions for a library |
get_job_status |
Check indexing job progress |
cancel_job |
Cancel running indexing job |
fetch_url |
Fetch URL and convert to markdown |
Configuration System
Configuration resolves via Zod schema with four layers: Defaults < Config File < Environment Variables < CLI Arguments
Key Settings:
# config.yaml
embedding:
provider: openai # or ollama, gemini, azure, aws
model: text-embedding-3-small
storage:
path: ~/.local/share/docs-mcp-server
server:
port: 6280
protocol: auto # stdio, http, or auto
Supported Embedding Providers
| Provider | Local/Cloud | Cost |
|---|---|---|
| OpenAI | Cloud | Paid |
| Ollama | Local | Free |
| Google Gemini | Cloud | Paid |
| Azure OpenAI | Cloud | Paid |
| AWS Bedrock | Cloud | Paid |
Comparison with Alternatives
| Feature | Docs MCP Server | Context7 | Nia | Ref.Tools |
|---|---|---|---|---|
| Open Source | Yes (MIT) | No | No | No |
| Self-Hosted | Yes | No | No | No |
| Privacy | Full (local) | Cloud | Cloud | Cloud |
| Custom Sources | Yes | Limited | Limited | Limited |
| Multi-Provider Embeddings | Yes | No | No | No |
| Version-Specific | Yes | Yes | Yes | Yes |
| Cost | Free + embeddings | Subscription | Subscription | Subscription |
Relevance to Claude Code Development
Direct Applications
- Documentation Grounding: Eliminate hallucinations when coding with unfamiliar libraries
- Version-Specific Context: Query docs for exact versions in project dependencies
- Local Privacy: Keep proprietary documentation indexed locally
- Multi-Format Support: Index internal docs in various formats (PDF, Word, etc.)
Patterns Worth Adopting
- Semantic Chunking: Two-phase splitting (semantic structure + size optimization)
- Hybrid Search: Combining vector similarity with full-text for better recall
- Protocol Auto-Detection: Automatic transport selection based on environment
- Write-Through Architecture: Immediate persistence for recovery capability
- Distributed Mode Design: Hub-spoke pattern for scalable processing
Integration Opportunities
- Claude Code Plugin: Create plugin that auto-indexes project dependencies
- Skill Enhancement: Ground skills in current documentation automatically
- RAG Pattern: Apply hybrid search approach to existing context systems
- Multi-Source Truth: Pattern for combining documentation from multiple sources
Complementary to Existing MCP Ecosystem
This fills a gap in the research directory's MCP ecosystem coverage:
- Narsil MCP: Code intelligence and security scanning
- OctoCode MCP: Research Driven Development with GitHub search
- Docs MCP Server: Documentation grounding and version-specific retrieval
References
- GitHub Repository: https://github.com/arabold/docs-mcp-server (accessed 2026-01-26)
- Official Website: https://grounded.tools (accessed 2026-01-26)
- npm Package: https://www.npmjs.com/package/@arabold/docs-mcp-server (accessed 2026-01-26)
- Architecture Documentation: https://github.com/arabold/docs-mcp-server/blob/main/ARCHITECTURE.md (accessed 2026-01-26)
- Installation Guide: https://github.com/arabold/docs-mcp-server/blob/main/docs/setup/installation.md
- MCP Protocol Specification: https://modelcontextprotocol.io/
Freshness Tracking
| Field | Value |
|---|---|
| Last Verified | 2026-01-26 |
| Version at Verification | v1.36.0 |
| GitHub Stars at Verification | 954 |
| npm Downloads at Verification | Not available |
| Next Review Recommended | 2026-04-26 (3 months) |
Change Detection Indicators:
- Monitor GitHub releases for version changes
- Check npm for new versions
- Review changelog for breaking changes
- Track MCP protocol compatibility updates
- Monitor for new embedding provider support