MCP - Model Context Protocol
Provides the API framework for the MCP server with JWT authentication support for secure user access.
Enables integration with local large language models like Mistral, allowing the MCP server to process conversational AI requests without relying on cloud services.
Used for data validation and schema definition in the MCP server's API routes and request handling.
Provides persistent storage for the MCP server to maintain user data and conversation state.
This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
🧠 MCP - Model Context Protocol
Complete project for a conversational application with:
✅ FastAPI + JWT
✅ Local LLM via Ollama (ex: Mistral)
✅ Context with vector memory (ChromaDB)
✅ Support for multiple users and sessions
✅ Automatic summary of long history
✅ Plugin system to perform real actions
🚀 How to rotate
1. Clone the project and create the environment
git clone <repo>
cd mcp
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt2. Configure .env
MODEL_NAME=mistral
VECTOR_DB_PATH=./chroma
DB_PATH=./mcp.db
CONTEXT_LIMIT=5
SUMMARY_TRIGGER=203. Launch Ollama
ollama run mistral4. Upload the server
chmod +x start.sh
./start.shRelated MCP server: RAG Context MCP Server
🛡️ Authentication
POST /auth/register: Create new user
POST /auth/login: Returns JWT token
Use the JWT token in requests to /mcp/chat.
🤖 Plugins
To call a plugin:
{
"session_id": "sessao01",
"prompt": "plugin: {\"name\": \"list_files\", \"args\": {\"path\": \"/etc\"}}"
}📁 Structure
app/
├── routes/ # Rotas da API
├── services/ # Lógica de negócio (MCP, plugins, memória)
├── db/ # Persistência (SQLite e vetorial)
├── models/ # Schemas Pydantic
├── plugins/ # Plugins executáveis pelo MCP
├── auth/ # Login, JWT, usuários📬 Contact
Developed by [Everson 🧠].
This server cannot be deployed
Maintenance
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