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.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCP - Model Context Protocolsummarize our last conversation about the new plugin architecture"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
🧠 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
Related MCP Connectors
A comprehensive Model Context Protocol (MCP) server that enables AI assistants to interact with yo…
Persistent memory, hybrid search and a goal graph for AI agents, over stdio or remote HTTP.
Memory for deep conversational context across any platform
past.dev is a long-term memory API for AI agents. Send it timestamped text such as emails, meeting transcripts and support tickets. Ask a question and get the current fact, the value it replaced and the source behind it. With this server, your assistant can recall and save memory and manage your past.dev account.
Related MCP Servers
- FlicenseNot gradedqualityDmaintenanceA server that enables seamless integration between local Ollama LLM instances and MCP-compatible applications, providing advanced task decomposition, evaluation, and workflow management capabilities.6-
- AlicenseNot gradedqualityDmaintenanceA lightweight server that provides persistent memory and context management for AI assistants using local vector storage and database, enabling efficient storage and retrieval of contextual information through semantic search and indexed retrieval.2MIT
- AlicenseNot gradedqualityDmaintenanceA persistent AI memory server that enables storage and retrieval of context and project artifacts across conversations. It features full-text search, version history, and automatic content chunking using local SQLite or hosted cloud storage.10 npmApache 2.0
- FlicenseNot gradedqualityDmaintenanceA production-grade memory server for LibreChat that stores conversation turns and distills durable memories like decisions, constraints, and assumptions. It provides hybrid retrieval and consistency auditing to ensure AI plans remain aligned with established context and previous decisions.-