Myco Brain
Self-hosted memory and knowledge-graph MCP server for AI agents. TypeScript on Postgres 16 + pgvector, 11 brain_* tools. Runs keyless: full-text and semantic…
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Self-hosted memory and knowledge-graph MCP server for AI agents. TypeScript on Postgres 16 + pgvector, 11 brain_* tools. Runs keyless: full-text and semantic…
Leverages the deepseek-r1 model to provide structured reasoning capabilities through specialized tools for analytical thinking, reflection with quality…
Provides persistent long-term memory capabilities through semantic indexing, retrieval, and search functions with support for multiple LLM providers and…
Persistent memory layer for AI agents with entity resolution, PII detection, AES-256-GCM encryption at rest, and hybrid search. Self-hosted. 100% on LoCoMo…
Shinobi gives every AI coding agent on your machine — and every cloud Claude session — one shared task spine, decision log, and searched dead-ends ledger…
Yamaru Hardware Probe gives Claude Desktop and other MCP clients real visibility into your machine. 10 expert tools: full hardware inventory, real-time…
The Model Context Protocol Server for NebulaGraph is an MCP server that provides LLM tooling systems with seamless access to NebulaGraph 3.x. It enables graph…
📄 The PDF intelligence layer for AI agents — Agent Document Twin, evidence-first extraction, visual crops, OCR provenance, trust reports, and benchmark-gated…
Bridges Apache Solr search indexes with vector embeddings for hybrid keyword and semantic document retrieval, enabling contextual searches against structured…
# MCP (Model Context Protocol) 서버 MCP 서버는 다양한 LLM(Large Language Model)을 통합 관리하고 표준화된 인터페이스를 제공하는 서비스입니다. 이 프로젝트는 DeepSeek와 Llama 모델을 통합하여 모델 간 전환이 용이하고, 컨텍스트…
Audit-grade memory backbone for agent teams. Bi-temporal facts (event time + transaction time, with recall(as_of=...) replay), 6-step deterministic retrieval…
Integrates Retrieval-Augmented Generation using Qdrant vector database and embeddings to enable semantic search and management of documentation.
A list of open-source AI projects you can use to generate income easily.
A custom server project built using the Model Context Protocol (MCP) in Python. This repository documents my learning, experiments, and development progress.
# 🔍 Semantic-Sift **The Reasoning-First Middleware for High-Fidelity Agentic Workflows.** [ through practical guides, clients, and servers I've built while learning about this new protocol.
# Phone-a-Friend MCP Server 🧠📞 An AI-to-AI consultation system that enables one AI to "phone a friend" (another AI) for critical thinking, long context…
# IntraIntel.ai - Multi-LLM Agent Coding Challenge This project implements a Multi-LLM Agent system in Python designed to answer medical questions. It…
Model Context Protocol (MCP) is a client-server protocol that enables communication between large language models (LLMs) and external tools or data sources. It…
# Integrating AI with Flutter: Creating AI Services with LlmServer and mcp_server ![Flutter and AI…
The Model Context Protocol (MCP) is a standardized way introduced by Anthropic for LLMs to interact with external tools, functions, and inject context. It…
This is a step‑by‑step tutorial that teaches how to build a Model Context Protocol (MCP) server and client from scratch using Python 3.11 and the uv package…
# Void MCP Server This project provides a Model Context Protocol (MCP) server for managing LLM context data. A small utility `run_local.py` can launch a local…