ai-mldeveloper-tools

Doclea MCP

by docleaai

Doclea MCP: persistent memory for AI assistants—store and retrieve architectural decisions, patterns and code insights u

Provides persistent memory for AI coding assistants, storing and retrieving architectural decisions, patterns, and solutions across sessions using semantic search, while also offering git integration for commit messages and code expertise mapping.

github stars

0

Persistent memory across AI sessionsSemantic search for code patternsGit integration included

best for

  • / Developers maintaining consistency across long projects
  • / Teams preserving architectural knowledge
  • / AI assistants that need project context memory

capabilities

  • / Store architectural decisions and patterns with semantic search
  • / Retrieve relevant code solutions across sessions
  • / Generate commit messages from code changes
  • / Map code expertise and knowledge domains
  • / Integrate with git repositories
  • / Search stored knowledge semantically

what it does

Gives AI coding assistants persistent memory across chat sessions, storing architectural decisions, code patterns, and solutions with semantic search.

about

Doclea MCP is an official MCP server published by docleaai that provides AI assistants with tools and capabilities via the Model Context Protocol. Doclea MCP: persistent memory for AI assistants—store and retrieve architectural decisions, patterns and code insights u It is categorized under ai ml, developer tools.

how to install

You can install Doclea MCP in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

Doclea MCP is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

@doclea/mcp

npm version License: MIT Node.js Bun

Local MCP server for Doclea — persistent memory for AI coding assistants.

Doclea gives your AI coding assistant (Claude Code, etc.) persistent memory across sessions. It remembers architectural decisions, patterns, solutions, and codebase context so you don't have to repeat yourself.

Features

  • Persistent Memory — Store decisions, patterns, solutions, and notes that persist across sessions
  • Semantic Search — Find relevant context using vector similarity search
  • Git Integration — Generate commit messages, PR descriptions, and changelogs from your history
  • Code Expertise Mapping — Identify code owners and suggest reviewers based on git blame analysis
  • Zero-Config Mode — Works immediately with no Docker or external services required
  • Auto-Detection — Automatically uses optimized Docker backends when available

Quick Start

Add to your Claude Code config (~/.claude.json or project .claude.json):

{
  "mcpServers": {
    "doclea": {
      "command": "npx",
      "args": ["@doclea/mcp"]
    }
  }
}

Restart Claude Code, navigate to your project, and ask:

Initialize doclea for this project

That's it! Doclea scans your codebase, git history, and documentation to bootstrap memories.

Installation Options

MethodCommandSetup TimeBest For
Zero-Confignpx @doclea/mcp<30 secondsQuick start, small projects
Optimizedcurl install.sh3-5 minutesProduction, large codebases
ManualClone & build5-10 minutesDevelopment, customization

Zero-Config (Recommended)

Works immediately with no Docker required. Uses embedded sqlite-vec for vectors and Transformers.js for embeddings.

First run downloads the embedding model (~90MB) which is cached for future use.

Optimized Installation (Docker)

For larger codebases with better performance:

curl -fsSL https://raw.githubusercontent.com/docleaai/doclea-mcp/main/scripts/install.sh | bash

This script:

  • Detects your OS and architecture
  • Installs prerequisites (Bun, Docker if needed)
  • Sets up Qdrant vector database and TEI embeddings service
  • Configures Claude Code automatically

Manual Installation

git clone https://github.com/docleaai/doclea-mcp.git
cd doclea-mcp
bun install
bun run build

Add to Claude Code (~/.claude.json):

{
  "mcpServers": {
    "doclea": {
      "command": "node",
      "args": ["/absolute/path/to/doclea-mcp/dist/index.js"]
    }
  }
}

For detailed setup instructions, see docs/INSTALLATION.md.

Usage Examples

Store Memories

Store this as a decision: We're using PostgreSQL for ACID compliance
in financial transactions. Tag it with "database" and "infrastructure".

Search Context

Search memories for authentication patterns

Git Operations

Generate a commit message for my staged changes
Create a PR description for this branch
Generate a changelog from v1.0.0 to HEAD

Code Expertise

Who should review changes to src/auth/?

MCP Tools

Memory Tools

ToolDescription
doclea_storeStore a memory (decision, solution, pattern, architecture, note)
doclea_searchSemantic search across memories
doclea_getGet memory by ID
doclea_updateUpdate existing memory
doclea_deleteDelete memory

Git Tools

ToolDescription
doclea_commit_messageGenerate conventional commit from staged changes
doclea_pr_descriptionGenerate PR description with context
doclea_changelogGenerate changelog between refs

Expertise Tools

ToolDescription
doclea_expertiseMap codebase expertise and bus factor risks
doclea_suggest_reviewersSuggest PR reviewers based on file ownership

Bootstrap Tools

ToolDescription
doclea_initInitialize project, scan git history, docs, and code
doclea_importImport from markdown files or ADRs

Memory Types

TypeUse Case
decisionArchitectural decisions, technology choices
solutionBug fixes, problem resolutions
patternCode patterns, conventions
architectureSystem design notes
noteGeneral documentation

Configuration

Doclea works out of the box with zero configuration. It auto-detects available backends:

  1. If Docker services (Qdrant/TEI) are running → uses them for better performance
  2. Otherwise → uses embedded sqlite-vec + Transformers.js

Custom Configuration

Create .doclea/config.json in your project root:

{
  "embedding": {
    "provider": "transformers",
    "model": "Xenova/all-MiniLM-L6-v2"
  },
  "vector": {
    "provider": "sqlite-vec",
    "dbPath": ".doclea/vectors.db"
  },
  "storage": {
    "dbPath": ".doclea/local.db"
  }
}

Embedding Providers

ProviderConfigNotes
transformers{ "provider": "transformers" }Default, no Docker
local{ "provider": "local", "endpoint": "http://localhost:8080" }TEI Docker
openai{ "provider": "openai", "apiKey": "..." }API key required
ollama{ "provider": "ollama", "model": "nomic-embed-text" }Local Ollama

Vector Store Providers

ProviderConfigNotes
sqlite-vec{ "provider": "sqlite-vec" }Default, no Docker
qdrant{ "provider": "qdrant", "url": "http://localhost:6333" }Docker service

Architecture

┌─────────────────────────────────────────────────────────┐
│                     Claude Code                         │
│                         ↓ MCP                           │
├─────────────────────────────────────────────────────────┤
│                   Doclea MCP Server                     │
│  ┌─────────┐ ┌─────────┐ ┌──────────┐ ┌───────────┐   │
│  │ Memory  │ │   Git   │ │Expertise │ │ Bootstrap │   │
│  │  Tools  │ │  Tools  │ │  Tools   │ │   Tools   │   │
│  └────┬────┘ └────┬────┘ └────┬─────┘ └─────┬─────┘   │
│       └───────────┴───────────┴─────────────┘          │
│                         ↓                              │
│  ┌──────────────┐ ┌──────────────┐ ┌──────────────┐   │
│  │   SQLite     │ │  Vector DB   │ │  Embeddings  │   │
│  │  (metadata)  │ │(sqlite-vec/  │ │(transformers/│   │
│  │              │ │   qdrant)    │ │    TEI)      │   │
│  └──────────────┘ └──────────────┘ └──────────────┘   │
└─────────────────────────────────────────────────────────┘

Development

# Install dependencies
bun install

# Run in development mode (hot reload)
bun run dev

# Run tests
bun test              # All tests
bun run test:unit     # Unit tests only
bun run test:integration  # Integration tests (requires Docker)

# Type check
bun run typecheck

# Lint
bun run lint          # Check
bun run lint:fix      # Auto-fix

# Build
bun run build

Troubleshooting

First startup is slow

The embedding model (~90MB) downloads on first run. Cached at:

  • Linux/macOS: ~/.cache/doclea/transformers
  • Windows: %LOCALAPPDATA%\doclea ransformers

macOS SQLite extension error

macOS ships with Apple's SQLite which doesn't support extensions:

brew install sqlite

The server auto-detects Homebrew SQLite.

MCP server not appearing in Claude

  1. Verify the path in config is absolute (manual installs)
  2. Check that bun run build completed successfully
  3. Restart Claude Code completely

See docs/INSTALLATION.md for more troubleshooting.

Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

# Fork and clone
git clone https://github.com/YOUR_USERNAME/doclea-mcp.git

# Create feature branch
git checkout -b feature/amazing-feature

# Make changes, test, and lint
bun test && bun run lint

# Commit and push
git commit -m 'feat: add amazing feature'
git push origin feature/amazing-feature

Roadmap

  • Cloud sync for team collaboration
  • VS Code extension
  • Additional embedding providers
  • Memory analytics dashboard

License

MIT © Quantic Studios


<p align="center"> <a href="https://doclea.ai">Website</a> • <a href="https://github.com/docleaai/doclea-mcp/issues">Issues</a> • <a href="https://github.com/docleaai/doclea-mcp/discussions">Discussions</a> </p>

FAQ

What is the Doclea MCP MCP server?
Doclea MCP is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Doclea MCP?
This profile displays 10 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.
MCP server reviews

Ratings

4.510 reviews
  • Shikha Mishra· Oct 10, 2024

    Doclea MCP is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Piyush G· Sep 9, 2024

    We evaluated Doclea MCP against two servers with overlapping tools; this profile had the clearer scope statement.

  • Chaitanya Patil· Aug 8, 2024

    Useful MCP listing: Doclea MCP is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Sakshi Patil· Jul 7, 2024

    Doclea MCP reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Ganesh Mohane· Jun 6, 2024

    I recommend Doclea MCP for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Oshnikdeep· May 5, 2024

    Strong directory entry: Doclea MCP surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Dhruvi Jain· Apr 4, 2024

    Doclea MCP has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Rahul Santra· Mar 3, 2024

    According to our notes, Doclea MCP benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Pratham Ware· Feb 2, 2024

    We wired Doclea MCP into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Yash Thakker· Jan 1, 2024

    Doclea MCP is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.