openrag-mcp 0.3.0

RETIRED — OpenRAG MCP is now built into the OpenRAG backend as a streamable-HTTP endpoint at /mcp. See README for migration.

OpenRAG MCP — Final Release Notice

This package (openrag-mcp) has been retired.

OpenRAG now ships a built-in Model Context Protocol server over streamable HTTP — no subprocess, no separate install, no API key in a subprocess env block. Connect your MCP client directly to your running OpenRAG instance.

The last published version of openrag-mcp on PyPI is the final release. No further updates will be made to this package.

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Migrating to streamable HTTP

The OpenRAG backend exposes an MCP endpoint at /mcp using the streamable-HTTP transport. Any MCP client that supports "url"-based server configs (Cursor, Claude Desktop, and the MCP SDK) can connect to it directly.

Prerequisites

• A running OpenRAG instance (v0.3.0 or later)
• An OpenRAG API key — create one in Settings → API Keys

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Cursor

Config file: ~/.cursor/mcp.json

Standard API key:

{
  "mcpServers": {
    "openrag": {
      "url": "https://your-openrag-instance.com/mcp",
      "headers": {
        "X-API-Key": "orag_your_api_key_here"
      }
    }
  }
}

IBM auth (when IBM_AUTH_ENABLED=true on the server):

{
  "mcpServers": {
    "openrag": {
      "url": "https://your-openrag-instance.com/mcp",
      "headers": {
        "X-Username": "your_ibm_username",
        "X-Api-Key": "your_ibm_api_key"
      }
    }
  }
}

Restart Cursor after saving the config.

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Claude Desktop

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json

Standard API key:

{
  "mcpServers": {
    "openrag": {
      "url": "https://your-openrag-instance.com/mcp",
      "headers": {
        "X-API-Key": "orag_your_api_key_here"
      }
    }
  }
}

IBM auth:

{
  "mcpServers": {
    "openrag": {
      "url": "https://your-openrag-instance.com/mcp",
      "headers": {
        "X-Username": "your_ibm_username",
        "X-Api-Key": "your_ibm_api_key"
      }
    }
  }
}

Restart Claude Desktop after editing the file.

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Available tools

All tools are auto-exposed from the /v1/ API and are available immediately after connecting:

Tool	Description
openrag_chat	Send a message and get a RAG-enhanced response. Supports chat_id and filter_id.
openrag_list_chats	List all chat conversations.
openrag_get_chat	Get a specific chat conversation by ID.
openrag_delete_chat	Delete a chat conversation by ID.
openrag_search	Semantic search over the knowledge base. Supports filters, score threshold, data sources.
openrag_ingest	Ingest documents (files, URLs, text) into the knowledge base. Returns a task_id.
openrag_get_task_status	Check the status of an ingestion task by task_id.
openrag_delete_document	Delete a document from the knowledge base by filename.
openrag_get_settings	Get current OpenRAG configuration (LLM, embeddings, chunk settings, system prompt).
openrag_update_settings	Update OpenRAG configuration. All fields are optional.
openrag_list_models	List available models for a provider (openai, anthropic, ollama, watsonx).
openrag_create_knowledge_filter	Create a knowledge filter to scope searches and chats.
openrag_search_knowledge_filters	Search knowledge filters by name or criteria.
openrag_get_knowledge_filter	Get a knowledge filter by ID.
openrag_update_knowledge_filter	Update an existing knowledge filter.
openrag_delete_knowledge_filter	Delete a knowledge filter by ID.

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Why streamable HTTP?

• No subprocess — your MCP client connects over HTTP; nothing to install or spawn locally.
• Full tool surface — document ingestion, task tracking, and knowledge filters are available from day one (previously listed as "coming later" in the stdio package).
• One auth model — the same API key or IBM credentials you use for the REST API work for MCP.
• Self-hosted and secure — the /mcp endpoint is part of your OpenRAG deployment; nothing leaves your network.

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License

Apache 2.0 — see LICENSE for details.