by docleaai
Doclea MCP: persistent memory for AI assistants—store and retrieve architectural decisions, patterns and code insights u
Gives AI coding assistants persistent memory across chat sessions, storing architectural decisions, code patterns, and solutions with semantic search.
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.
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.
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.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
I recommend Doclea MCP for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
Strong directory entry: Doclea MCP surfaces stars and publisher context so we could sanity-check maintenance before adopting.
I recommend Doclea MCP for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
Doclea MCP is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Strong directory entry: Doclea MCP surfaces stars and publisher context so we could sanity-check maintenance before adopting.
Doclea MCP reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
Useful MCP listing: Doclea MCP is the kind of server we cite when onboarding engineers to host + tool permissions.
Doclea MCP is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
We wired Doclea MCP into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
Doclea MCP is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
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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.
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.
| Method | Command | Setup Time | Best For |
|---|---|---|---|
| Zero-Config | npx @doclea/mcp | <30 seconds | Quick start, small projects |
| Optimized | curl install.sh | 3-5 minutes | Production, large codebases |
| Manual | Clone & build | 5-10 minutes | Development, customization |
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.
For larger codebases with better performance:
curl -fsSL https://raw.githubusercontent.com/docleaai/doclea-mcp/main/scripts/install.sh | bash
This script:
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.
Store this as a decision: We're using PostgreSQL for ACID compliance
in financial transactions. Tag it with "database" and "infrastructure".
Search memories for authentication patterns
Generate a commit message for my staged changes
Create a PR description for this branch
Generate a changelog from v1.0.0 to HEAD
Who should review changes to src/auth/?
| Tool | Description |
|---|---|
doclea_store | Store a memory (decision, solution, pattern, architecture, note) |
doclea_search | Semantic search across memories |
doclea_get | Get memory by ID |
doclea_update | Update existing memory |
doclea_delete | Delete memory |
| Tool | Description |
|---|---|
doclea_commit_message | Generate conventional commit from staged changes |
doclea_pr_description | Generate PR description with context |
doclea_changelog | Generate changelog between refs |
| Tool | Description |
|---|---|
doclea_expertise | Map codebase expertise and bus factor risks |
doclea_suggest_reviewers | Suggest PR reviewers based on file ownership |
| Tool | Description |
|---|---|
doclea_init | Initialize project, scan git history, docs, and code |
doclea_import | Import from markdown files or ADRs |
| Type | Use Case |
|---|---|
decision | Architectural decisions, technology choices |
solution | Bug fixes, problem resolutions |
pattern | Code patterns, conventions |
architecture | System design notes |
note | General documentation |
Doclea works out of the box with zero configuration. It auto-detects available backends:
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"
}
}
| Provider | Config | Notes |
|---|---|---|
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 |
| Provider | Config | Notes |
|---|---|---|
sqlite-vec | { "provider": "sqlite-vec" } | Default, no Docker |
qdrant | { "provider": "qdrant", "url": "http://localhost:6333" } | Docker service |
┌─────────────────────────────────────────────────────────┐
│ Claude Code │
│ ↓ MCP │
├─────────────────────────────────────────────────────────┤
│ Doclea MCP Server │
│ ┌─────────┐ ┌─────────┐ ┌──────────┐ ┌───────────┐ │
│ │ Memory │ │ Git │ │Expertise │ │ Bootstrap │ │
│ │ Tools │ │ Tools │ │ Tools │ │ Tools │ │
│ └────┬────┘ └────┬────┘ └────┬─────┘ └─────┬─────┘ │
│ └───────────┴───────────┴─────────────┘ │
│ ↓ │
│ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │
│ │ SQLite │ │ Vector DB │ │ Embeddings │ │
│ │ (metadata) │ │(sqlite-vec/ │ │(transformers/│ │
│ │ │ │ qdrant) │ │ TEI) │ │
│ └──────────────┘ └──────────────┘ └──────────────┘ │
└─────────────────────────────────────────────────────────┘
# 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
The embedding model (~90MB) downloads on first run. Cached at:
~/.cache/doclea/transformers%LOCALAPPDATA%\doclea ransformersmacOS ships with Apple's SQLite which doesn't support extensions:
brew install sqlite
The server auto-detects Homebrew SQLite.
bun run build completed successfullySee docs/INSTALLATION.md for more troubleshooting.
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
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.