Self-hosted, plug-and-play MCP gateway for agentic productivity. One endpoint to connect all your tools (Jira, Confluence, Microsoft 365, Obsidian, and more) to any AI assistant.
agenticflow gives AI agents a single, intelligent MCP endpoint that routes to all your productivity tools. It adds:
- Unified gateway via MCPJungle — one config in Claude/Cursor, access everything
- Markdown & Obsidian memory — semantic search and time-based retrieval over your personal knowledge vault or Markdown folders
- Skill/tool discovery — agents find the right tool by describing intent, not by knowing tool names
- Plug-and-play — add new services without reconfiguring your AI client
- Model Compatibility — Insights on how different LLMs (Claude, GPT, Gemini, Sonar) behave with agenticflow tools
See docs/ROADMAP.md for current development priorities and vision.
AI Client (Claude / Cursor / Custom)
│
▼ single MCP endpoint
MCPJungle Gateway :18080
│
┌──────┼──────────┬──────────┐
▼ ▼ ▼ ▼
[Memory] [Jira] [Confluence] [Discovery]
Obsidian Work Docs Semantic
Notes Items Search Tool RAG
- Docker + Docker Compose
- Node.js (v18+) and npm
- An Obsidian vault or any Markdown folder (any structure)
Run the installation script from the repository root. This will automatically build the CLI and launch the guided setup wizard to configure your environment, master password, and any external integrations (like Jira/Confluence):
git clone https://github.com/YOUR_USERNAME/agenticflow.git
cd agenticflow
./setup.shNote: If your terminal says
agenticflow: command not foundafter setup completes, your system'sPATHis likely missing the global npm bin directory (very common on Linux servers). Run this to fix it permanently:export PATH="$(npm config get prefix)/bin:$PATH" echo 'export PATH="$(npm config get prefix)/bin:$PATH"' >> ~/.bashrc
The wizard will:
- Configure your
.envand Obsidian vault path. - Store your Master Password securely.
- Automatically build and start the Docker containers.
- Let you index your vault for the first time.
(If you ever need to stop or start the cluster manually, just run agenticflow up or agenticflow down)
⚠️ Important: Direct SSE is currently not supported. Due to proxy routing complexities, AI clients that attempt to connect directly via SSE (e.g., native Gemini CLI) may fail to resolve the return endpoints correctly. You must use anmcp-remotebridge (or similar STDIO-to-SSE adapter) to connect.
Claude Desktop (~/Library/Application Support/Claude/claude_desktop_config.json):
{
"mcpServers": {
"agenticflow": {
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-remote", "http://localhost:18080/mcp"]
}
}
}Cursor:
- Go to Settings > MCP
- Add new server
- Type:
command - Command:
npx - Args:
-y @modelcontextprotocol/server-remote http://localhost:18080/mcp
That's it. All your tools are now available.
| Service | Status |
|---|---|
| Obsidian Memory (semantic + temporal) | 🔧 In development |
| Jira | ✅ Via Atlassian MCP |
| Confluence | ✅ Via Atlassian MCP |
| SharePoint / Microsoft 365 | 🔧 In development |
| Filesystem | ✅ Bundled |
| n8n | ✅ Via n8n-mcp |
| Miro | 📋 Planned |
| MS Fabric | 📋 Planned |
If you are running agenticflow on a device with limited CPU cores (e.g. 2 cores) and notice 100% CPU usage during start or when indexing, you can enable AGENTICFLOW_LOW_RESOURCE_MODE=true in your .env file. This limits the local embedding models to a single thread, preventing the container from starving the host OS.
Works with any Markdown folder or Obsidian vault layout. The memory server indexes by content, not structure. It automatically detects Obsidian vaults to enable specific features like > [!ai] callouts. See docs/obsidian-setup.md for the recommended setup if you're starting fresh.
See CONTRIBUTING.md and our Development Guide for testing and isolated worktree workflows. The project is structured so you only need to configure your .env and servers.d/ configuration files — nothing personal ever lands in the repo.
MIT