Connapse
Active·★ 12·MIT·Updated 2026-05-28
★ Trending★ RAG / Knowledge Base★ LLM Infra
Open-source, self-hosted knowledge backend for AI agents — hybrid search (vector + keyword), MCP server, 5 connectors, Docker-ready
Connapse is an open-source knowledge backend that gives AI agents persistent, searchable memory. Upload documents or connect to existing storage like Amazon S3, Azure Blob Storage, or local filesystems. Agents query and build their own research corpus via MCP, REST API, or CLI, deployable in 60 seconds with Docker.
#ai#ai-agents#blazor#docker#document-management#dotnet#embeddings#generative-ai
01
Features
01Container-Isolated Knowledge with per-project vector indexes and storage connectors
02Hybrid Search combining vector similarity and keyword full-text with configurable fusion
03Multi-Provider AI - swap between Ollama, OpenAI, Azure OpenAI, and Anthropic at runtime
04Index Your Existing Storage - connect MinIO, local filesystem, Amazon S3, or Azure Blob Storage
054 Access Surfaces - Web UI, REST API, CLI, and MCP server with 11 tools for Claude
02
Compatibility
Windows
Windows
Verified via docs
Linux
Linux
Verified via docs
macOS
macOS
Verified via docs
Docker
Docker
Verified via docs
03
Quick start
1
$ git clone https://github.com/Destrayon/Connapse.git
2
$ cd Connapse
3
$ docker-compose up -d
04
Use cases
↳AI agent developers needing a knowledge backend for query and curation via MCP or REST
↳.NET / Azure teams wanting a RAG platform that fits their existing stack and cloud identity
↳Enterprise teams requiring project-isolated knowledge bases with RBAC and audit trails
05
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Comments
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- SSage GarciaApr 13, 2026
Works as a knowledge backbone that agent capabilities build on.
- RRemy PatelApr 8, 2026
Open-source, self-hosted hybrid search knowledge backend for AI agents.
- AAlex LeeMar 21, 2026
Good for teams who want a private, capable knowledge base without cloud dependencies.
- RRowan WhiteMar 14, 2026
Hybrid vector search combines semantic and keyword retrieval for better results.