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Openclaude MCP

Controls local Ollama sessions through MCP, with multimodal prompts, memory consolidation, hybrid planning, and fleet monitoring.

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Overview

openclaude-mcp connects FastMCP tools to the OpenClaude CLI and a locally running Ollama instance. It manages concurrent sessions, accepts text or image prompts, reports model and session state, and can persist usage data across restarts. Optional KAIROS memory consolidation, ULTRAPLAN cloud handoff, and fleet monitoring extend the local workflow. Reach for it when an agent needs to operate Ollama-backed OpenClaude sessions through MCP, REST, or the included dashboard.

Use cases

  • Manage multiple local Ollama sessions from an MCP client
  • Send image-based prompts to vision-capable local models
  • Consolidate session information into persistent memory
  • Inspect model VRAM, load state, and fleet activity
  • Run hybrid cloud-local planning cycles

Key features

  • Concurrent Ollama session management
  • Text and image prompt handling
  • KAIROS background memory consolidation
  • ULTRAPLAN hybrid planning
  • Fleet status and dashboard tools
  • SSE and REST transports

Tools16

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Self-reported~192 tokens of context

Security & health

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Adoption & maintenance

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GitHub stars7Stargazers on the source repository.
Last commit3d agoMost recent push to the default branch.
Tools exposed16Callable tools this server registers over MCP.

How Openclaude MCP works

What openclaude-mcp does

openclaude-mcp provides an MCP control plane for OpenClaude sessions backed by Ollama. It can create sessions, send prompts, inspect progress and usage, enumerate active sessions, and stop sessions when they are no longer needed. Multiple sessions can run concurrently, with persistence and usage analytics for prompts, output characters, estimated tokens, and elapsed time.

The server also exposes controls for Ollama models and optional supporting services. Agents can list available models, choose the default model for new sessions, and inspect VRAM and load status. Image input is supported through a separate multimodal tool for PNG, JPEG, WebP, and GIF files when the selected Ollama model supports vision.

KAIROS provides asynchronous background memory consolidation into MEMORY.md, with state retained across restarts. ULTRAPLAN supports a hybrid planning flow that can hand complex reasoning to a cloud Opus or Sonnet model while leaving execution local. Fleet tools expose either a dashboard-oriented view or raw status data, and the caregiver alert tool can notify caregivers about high-risk interactions.

How it works

A FastMCP 3.2 Python server coordinates the sessions, model routing, persistence, KAIROS controller, and event bus. It launches the OpenClaude CLI as a subprocess and communicates with it over stdio using newline-delimited JSON. The CLI uses Ollama on its local service at port 11434.

MCP clients connect through the server's SSE endpoint at http://localhost:10932/sse. The same backend also exposes a REST bridge for the React web application and command-line requests. Server-sent events provide real-time updates to the web interface, which includes fleet status, terminal output, system logs, KAIROS state, and an API playground.

The default backend port is 10932, while the fleet dashboard is served at port 10933. Health information is available at /api/health, and event updates are available at /api/events.

Setup and configuration

The documented quick-start path is to clone the repository, enter its directory, and run just. just bootstrap installs dependencies; just serve or just dev starts the service. A PowerShell setup path is also available with setup.ps1 followed by start.ps1, and Docker Compose can start the stack with docker compose up.

The runtime requires Ollama running locally, Node.js 20 or newer, Python 3.13 or newer with uv, and at least one downloaded local model. Examples include gemma4:26b and qwen3.5:35b-a3b.

Configuration includes OPENCLAUDE_MCP_PORT for the backend port, OPENCLAUDE_MCP_TOKEN for optional REST authentication, OPENCLAUDE_DIR for the OpenClaude source location, and OPENCLAUDE_CONFIG_DIR for persistent data. OPENCLAUDE_ULTRAPLAN_MODEL selects the Anthropic model used by ULTRAPLAN. KAIROS polling and consolidation limits can be adjusted with KAIROS_POLL_SECONDS and KAIROS_MAX_CONSOLIDATIONS; CAREGIVER_WEBHOOK_URL configures webhook delivery for caregiver alerts.

Tools and capabilities

The MCP interface contains tools for the following operations:

  • Create, prompt, inspect, list, and stop Ollama-backed sessions.
  • Send text together with supported image formats through send_multimodal.
  • Enable, disable, and inspect the KAIROS consolidation log.
  • List Ollama models, set the default model, and inspect model status.
  • Run a ULTRAPLAN hybrid planning cycle.
  • View a prepared fleet dashboard or retrieve raw fleet status JSON.
  • Send a caregiver alert for a high-risk interaction.

The web application adds real-time SSE updates, an xterm.js terminal, system log viewing, KAIROS status, and interactive API examples that call the backend and display response timing.

Limitations and notes

Local operation depends on Ollama, the OpenClaude CLI, and a compatible model being available. Multimodal requests require a vision-capable Ollama model. ULTRAPLAN can use a cloud Opus or Sonnet handoff, so it is distinct from an entirely local session. REST authentication is configured separately through OPENCLAUDE_MCP_TOKEN and is disabled when that variable is unset. The project is licensed under MIT.

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Frequently Asked Questions about Openclaude MCP

openclaude-mcp is an MCP server that connects the OpenClaude CLI to locally running Ollama models. Its main tools create and manage sessions, send text or multimodal prompts, inspect status, control models, run KAIROS memory consolidation, perform ULTRAPLAN planning, and report fleet state through FastMCP.

Clone the repository and run `just`, or use `just bootstrap` followed by `just serve` or `just dev`. Without `just`, run `setup.ps1` and then `start.ps1`; Docker Compose is also supported with `docker compose up`.

It requires a locally running Ollama service, Node.js 20 or newer, Python 3.13 or newer with `uv`, and at least one pulled local model. The OpenClaude CLI is launched as a subprocess by the server.

Yes, `send_multimodal` accepts text with PNG, JPEG, WebP, or GIF images. The selected Ollama model must support vision for these requests to work.

Yes, Claude Desktop can connect through the server's SSE endpoint at `http://localhost:10932/sse`. The architecture also names Cursor and VS Code as MCP clients.

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