ProjectContext
БесплатноНе проверенA high-performance MCP server providing long-term memory storage with semantic and keyword search, along with a structured agenda engine for task management.
Описание
A high-performance MCP server providing long-term memory storage with semantic and keyword search, along with a structured agenda engine for task management.
README
Improved Successor of AgentMemory
A high-performance MCP (Model Context Protocol) server providing long-term memory storage with semantic and keyword search capabilities, along with a structured agenda engine for task management.
Features
- Fast Semantic Search: Uses
fastembedwithBAAI/bge-small-en-v1.5for fast startup and low memory usage - Hybrid Search: Combines keyword (FTS5) and vector search using Reciprocal Rank Fusion (RRF)
- Agenda Engine: Task management with full-text search for plans and todo lists
- MCP Prompts: Specialized workflows for onboarding, feature planning, and memory maintenance
- Persistent Storage: SQLite-based storage with
sqlite-vecextension - Sub-200ms Queries: Keeps embedding model in memory for fast response times
- MCP Native: Exposes tools, resources, and prompts natively for AI agents
Installation
# Clone the repository
git clone <repo-url>
cd projectcontext
# Install dependencies with uv
uv sync
# Or install globally
uv pip install -e .
Usage
Running the Server
# Run directly
projectcontext
# Or with uv
uv run projectcontext
MCP Configuration
Add to your MCP client configuration (e.g., mcp.json):
{
"mcpServers": {
"projectcontext": {
"command": "uv",
"args": ["run", "projectcontext"],
"cwd": "/path/to/projectcontext"
}
}
}
Or using the installed script:
{
"mcpServers": {
"projectcontext": {
"command": "projectcontext"
}
}
}
MCP Tools
Memory Engine Tools
save_memory: Save a memory with category, topic, and content.query_memory: Search memories using hybrid semantic/keyword search.update_memory: Modify an existing memory by ID.delete_memory: Remove a memory by ID.
Agenda Engine Tools
create_agenda: Create a new multi-step plan or todo list.list_agendas: Show all active or inactive agendas.get_agenda: Retrieve detailed task information for a specific agenda.search_agendas: Search plans by title or description.update_task: Mark tasks as completed or pending.update_agenda: Modify agenda metadata or add new tasks.delete_agenda: Remove inactive agendas.
MCP Resources
projectcontext://usage-guidelines
Provides comprehensive documentation for AI agents on how to effectively use the Memory and Agenda engines, including categorization best practices and hallucination prevention.
projectcontext://schemas/{tool}
Provides the JSON schema for a specific tool. This is useful for AI agents to understand the required and optional parameters for each tool.
MCP Prompts
ProjectContext includes built-in prompts to guide AI agents through complex workflows:
setup_project_context: Templates for initializing a new project's tech stack, goals, and conventions.plan_feature_implementation: A structured workflow for searching existing context and creating a multi-step agenda for new features.summarize_and_remember: Distills conversation history into structured memories while avoiding duplicates.debug_with_history: A troubleshooting workflow that leverages pastbug_fixmemories and system context.maintain_memory_health: A proactive maintenance workflow for identifying and cleaning up outdated or redundant information.
Architecture
Technology Stack
- Framework: FastMCP (Python MCP library)
- Embeddings: fastembed (
BAAI/bge-small-en-v1.5, 384-dim) - Database: SQLite with
sqlite-vecandFTS5extensions - Communication: JSON-RPC over stdio
Storage Location
The databases are stored in the .ctxhub/ directory in the git root (or current working directory).
memory.sqlite: Memory Engine databaseagenda.sqlite: Agenda Engine database
Development
Project Structure
projectcontext/
├── src/
│ └── projectcontext/
│ ├── __init__.py # Package initialization
│ ├── server.py # MCP Server (Tools, Prompts, Resources)
│ ├── memory.py # Memory Engine Logic
│ ├── agenda.py # Agenda Engine Logic
│ └── database.py # Database Utilities
├── pyproject.toml
└── .ctxhub/ # Databases
Testing
# Quick start: runs main tests and offers to start server
./quickstart.sh
# Run specific tests manually
uv run python tests/test_server.py
uv run python tests/test_updates.py
MCP Inspector
npx @modelcontextprotocol/inspector uv run projectcontext
License
GPL-3.0-or-later
Установка ProjectContext
У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.
▸ github.com/asd-noor/projectcontextFAQ
ProjectContext MCP бесплатный?
Да, ProjectContext MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для ProjectContext?
Нет, ProjectContext работает без API-ключей и переменных окружения.
ProjectContext — hosted или self-hosted?
Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.
Как установить ProjectContext в Claude Desktop, Claude Code или Cursor?
Открой ProjectContext на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
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