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  1. Home
  2. 🧠 Knowledge & Memory
  3. Connapse
Connapse logo
Health: ActiveRecent health check succeeded.Last checked 9/9/2026, 3:33:03 PM

Connapse

User RatingsBe the first to rate and review this MCP server!
View Repository17 GitHub StarsTotal stargazers on GitHub for the source repository (17 stars).Visit Website
knowledge-basesearchmemoryself-hostedmcp

Self-hosted knowledge backend with hybrid search, isolated indexes, and MCP access for persistent agent memory.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

One-click editor setup isn’t available for this listing yet β€” we don’t have a confirmed install command, and we’d rather show nothing than point your editor at the wrong package or host. Follow the project’s own setup instructions, linked above.

Manual Client & Custom JSON ConfigExpand JSON β–Ύ
No confirmed setup config for this listing yet. We only publish a config block when the install details come from the project itself β€” its README, its docs, or a verified owner. We haven’t found those for Destrayon/Connapse, and we’d rather show nothing than a guess you’d paste into your client. Follow the project’s own setup instructions for the current steps.
Install Directory Badge Claim listing Alternatives🧠 More in Knowledge & Memory

Overview

Connapse stores documents and searchable knowledge for AI agents through MCP tools, a REST API, or a CLI. It supports uploads, local filesystems, Amazon S3, and Azure Blob Storage, using hybrid vector and keyword search with source citations. Use it when agents need a private, persistent knowledge base deployed with Docker.

Use cases

β€’Store documents for persistent agent memory
β€’Search research corpora with vector and keyword queries
β€’Connect existing S3 or Azure Blob Storage sources
β€’Query knowledge bases through MCP
β€’Manage indexed content through the CLI

Key features

β€’11 MCP tools
β€’Hybrid vector and keyword search
β€’Container-isolated indexes
β€’Document uploads and source ingestion
β€’REST API and CLI access
β€’Runtime embedding and search configuration

Capabilities & Tool Schemas

Inspect callable tools, capabilities, and parameters exposed to AI agents by Connapse.

Extracted Tool Capabilities
11 MCP tools
Hybrid vector and keyword search
Container-isolated indexes
Document uploads and source ingestion
REST API and CLI access
Runtime embedding and search configuration

Documentation Overview

Connapse logo

Stop losing context between AI sessions. Give your agents persistent, searchable memory.

License: MIT .NET Build Tests PRs Welcome GitHub Issues GitHub Stars Connapse MCP server Docker

Connapse demo β€” upload a PDF, search with hybrid vector and keyword search, get results with source citations in seconds

Your AI agents forget everything between sessions. Connapse fixes that.

Every time you start a new conversation, your AI agent starts from zero β€” no memory of past research, no access to your documents, no accumulated knowledge. Connapse is an open-source knowledge backend that gives agents persistent, searchable memory. Upload documents or point it at your existing Amazon S3 buckets or local filesystems. Agents query and build their own research corpus via 11 MCP tools, REST API, or CLI. Container-isolated, hybrid search (vector + keyword), self-hosted and private. Deploy in 60 seconds with Docker. Built on .NET 10.

πŸ€– AI Agent Integration β€” Claude queries and builds your knowledge base via MCP

Claude querying Connapse knowledge base via MCP server β€” asks about preventing cascading failures in microservices, gets structured answer with circuit breaker pattern details cited from distributed-systems-notes.md

AI agents query your knowledge base through the MCP server, receiving structured answers with source citations from your documents.

πŸŽ›οΈ Your Knowledge, Your Rules β€” Runtime configuration without restarting

Connapse settings panel β€” switching embedding providers, adjusting chunking parameters, and configuring search settings at runtime without restart

Switch embedding providers, tune chunking parameters, and configure search β€” all at runtime, without restarting.


πŸ“¦ Quick Start

bash
git clone https://github.com/Destrayon/Connapse.git && cd Connapse && docker-compose up -d
# Open http://localhost:5001

Prerequisites

  • Docker & Docker Compose
  • .NET 10 SDK (for development)
  • (Optional) Ollama for local embeddings

Run with Docker Compose

server.ts
# Clone the repository
git clone https://github.com/Destrayon/Connapse.git
cd Connapse

# Set required auth environment variables (or use a .env file)
export CONNAPSE_ADMIN_EMAIL=admin@example.com
export CONNAPSE_ADMIN_PASSWORD=YourSecurePassword123!
export Identity__Jwt__Secret=$(openssl rand -base64 64)

# Start all services (PostgreSQL, MinIO, Web App)
docker-compose up -d

# Open http://localhost:5001 β€” log in with the admin credentials above

The first run will:

  1. Pull Docker images (~2-5 minutes)
  2. Initialize PostgreSQL with pgvector extension and run EF Core migrations
  3. Create MinIO buckets
  4. Seed the admin account (from env vars) and start the web application

Development Setup

bash
# Start infrastructure only (database + object storage)
docker-compose up -d postgres minio

# Run the web app locally
dotnet run --project src/Connapse.Web

# Run all tests
dotnet test

# Run just unit tests
dotnet test --filter "Category=Unit"

Command-line client

The connapse CLI is published separately at Destrayon/connapse-cli.

Install:

bash
dotnet tool install -g Connapse.CLI
# or: download a binary from https://github.com/Destrayon/connapse-cli/releases/latest

Get started:

bash
connapse auth login --server https://localhost:5001
connapse --help

Using with Claude (MCP)

Connapse includes a Model Context Protocol (MCP) server for integration with Claude and any MCP client.

Setup: Create an agent API key via the web UI (Settings β†’ Agent API Keys), then add the config snippet for your client:

Claude Code (CLI)
Terminal
claude mcp add connapse --transport streamable-http http://localhost:5001/mcp --header "X-Agent-Api-Key: YOUR_API_KEY"
Claude Desktop

Add to your claude_desktop_config.json:

config.json
{
  "mcpServers": {
    "connapse": {
      "transport": "streamable-http",
      "url": "http://localhost:5001/mcp",
      "headers": {
        "X-Agent-Api-Key": "YOUR_API_KEY"
      }
    }
  }
}
VS Code / Cursor

Add to your .vscode/settings.json (VS Code) or Cursor MCP config:

config.json
{
  "mcp": {
    "servers": {
      "connapse": {
        "transport": "streamable-http",
        "url": "http://localhost:5001/mcp",
        "headers": {
          "X-Agent-Api-Key": "${input:connapseApiKey}"
        }
      }
    }
  }
}

VS Code will prompt for the API key on first use.

The MCP server exposes:

ToolDescription
container_createCreate a new container for organizing files
container_listList all containers with document counts
container_deleteDelete a container
container_statsGet container statistics (documents, chunks, storage, embeddings)
upload_fileUpload a single file to a container
bulk_uploadUpload up to 100 files in one operation
list_filesList files and folders at a path
get_documentRetrieve full parsed text content of a document
delete_fileDelete a single file from a container
bulk_deleteDelete up to 100 files in one operation
search_knowledgeSemantic, keyword, or hybrid search within a container

Full reference: See docs/mcp-tools.md for parameter tables, return formats, error cases, and usage examples.

Containers and sources: container_list tags each scope managed or source. A source is an external system Connapse mirrors read-only β€” searchable, but never browsable and never writable. list_files and every write tool resolve containers only; pass a source id and they report it as not found. See docs/connectors.md.

Example prompts β€” what to ask your agent
  • "Create a container called 'project-research' for my architecture notes"
  • "Upload all the PDFs in my downloads folder to the project-research container"
  • "Search my project-research container for information about rate limiting strategies"
  • "List all files in the /notes/ folder of my project-research container"
  • "Get the full text of distributed-systems-notes.md from project-research"
  • "Delete meeting-2026-03-14.md from project-research and upload this updated version"
  • "Delete all files in the /drafts/ folder of project-research"
  • "How many documents and chunks are in my project-research container?"
Troubleshooting

Connection refused on localhost:5001 β€” Docker not running or port conflict. Check docker compose ps and docker compose logs web.

401 Unauthorized / API key not working β€” Verify the key in Settings > Agent API Keys. Keys are shown once at creation.

Tools not appearing in Claude β€” Restart your MCP client after config changes. Verify endpoint with curl http://localhost:5001/mcp.

Uploads failing or timing out β€” Check file type is in the allowlist. Max file size depends on server config.

Search returns no results β€” Documents need time to embed after upload. Check container stats for embedding progress.


πŸš€ Features

Read the full README β†’View source on GitHub β†’

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks β€” not a rating.

GitHub stars
17
Stargazers on the source repository.
Last commit
2d ago
Most recent push to the default branch.
Directory activity
2 views
Config copies, upvotes, and views on AllMCPs.

Reviews

No reviews yet β€” be the first to share how this listing worked for you.

Frequently Asked Questions about Connapse

Agents can use its MCP server, REST API, or command-line client.

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Technical Specs & Signals

Category🧠Knowledge & Memory
PricingFree
More technical detailsExpand β–Ύ
AuthAPI key
LicenseMIT
ClientsClaude Desktop
Last updatedSep 9, 2026
10/10 checks healthy over the last 33d
Views2
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars17
GitHub Star CountTotal stargazers on GitHub representing community popularity (17 stars).
Last commit2d ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Sep 9, 2026
47Quality signal: Fair Β· 47/100How this signal is calculated β–Ύ
Server availabilityNot measured

Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools19/30
Adoption & activity6/15
Community engagement0/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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