Ragora MCP Server

Search your knowledge bases from any AI assistant using the Model Context Protocol.

Ragora's MCP server is a hosted cloud service — no local installation required. Just configure your AI tool with the server URL and your API key.

Server URL: https://mcp.ragora.app/mcp

Quick Start

1. Get an API Key

2. Connect Your AI Tool

Claude Desktop

Option 1: CLI (recommended)

claude mcp add --transport http ragora https://mcp.ragora.app/mcp \
  --header "Authorization: Bearer sk_live_your_key_here"

Option 2: Config file

Add to ~/Library/Application Support/Claude/claude_desktop_config.json (Mac) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "ragora": {
      "type": "http",
      "url": "https://mcp.ragora.app/mcp",
      "headers": {
        "Authorization": "Bearer sk_live_your_key_here"
      }
    }
  }
}

Claude Code

claude mcp add --transport http ragora https://mcp.ragora.app/mcp \
  --header "Authorization: Bearer sk_live_your_key_here"

Cursor

Add to .cursor/mcp.json in your project root:

{
  "mcpServers": {
    "ragora": {
      "type": "http",
      "url": "https://mcp.ragora.app/mcp",
      "headers": {
        "Authorization": "Bearer sk_live_your_key_here"
      }
    }
  }
}

VS Code / GitHub Copilot

Add to .vscode/mcp.json in your project root:

{
  "mcpServers": {
    "ragora": {
      "type": "http",
      "url": "https://mcp.ragora.app/mcp",
      "headers": {
        "Authorization": "Bearer sk_live_your_key_here"
      }
    }
  }
}

Windsurf

Add to ~/.codeium/windsurf/mcp_config.json:

{
  "mcpServers": {
    "ragora": {
      "serverUrl": "https://mcp.ragora.app/mcp",
      "headers": {
        "Authorization": "Bearer sk_live_your_key_here"
      }
    }
  }
}

Any MCP Client

Ragora uses Streamable HTTP transport. Point any MCP-compatible client to:

URL: https://mcp.ragora.app/mcp
Method: POST
Header: Authorization: Bearer sk_live_your_key_here

Available Tools

Tool	Description
`discover_collections`	List all knowledge bases you have access to, with descriptions, stats, and usage examples
`search`	Search across all your knowledge bases at once
`search_collection`	Search a specific collection by name, with optional tag/metadata filters

Tool Parameters

search(query, top_k?)

query (required): Natural language search query
top_k (optional): Number of results to return (default: 5)

search_collection(collection_name, query, top_k?, custom_tags?, filters?)

collection_name (required): Collection name or slug (use discover_collections to find names)
query (required): Natural language search query
top_k (optional): Number of results (default: 5)
custom_tags (optional): Tags to scope retrieval
filters (optional): Metadata filters

Dynamic Collection Tools

For each collection you have access to, dedicated tools are generated using the collection's slug:

search_{slug} — semantic search with optional version, tags, and filters
get_topic_{slug} — retrieve information about a specific topic
list_versions_{slug} — list available documentation versions

For example, a collection called "Employee Handbook" gets:

search_employee_handbook
get_topic_employee_handbook
list_versions_employee_handbook

Configure tool names and descriptions in the Ragora dashboard under Collection > MCP Settings.

Usage Examples

Search all collections:

"Search my docs for webhook event handling"

Search a specific collection:

"Look up the refund policy in the employee handbook"

Discover what's available:

"What workspaces do I have, and what's in them?"

How It Works

Your AI Tool                        Ragora Cloud
┌──────────────────┐               ┌──────────────────┐
│ Claude / Cursor  │   HTTP POST   │  MCP Server      │
│ / VS Code / etc  │──────────────>│  (Streamable HTTP)│
└──────────────────┘    /mcp       └────────┬─────────┘
                                            │
                                   ┌────────▼─────────┐
                                   │  Gateway API      │
                                   │  (Auth + Search)  │
                                   └────────┬─────────┘
                                       ┌────┴────┐
                                       ▼         ▼
                                   Postgres    Qdrant
                                   (metadata)  (vectors)

No local install — connect directly via HTTP
Multi-tenant — your API key determines which collections you can access
Dynamic tools — tools are generated based on your accessible collections
Hybrid search — dense (E5-Large) + sparse (BM25) with reciprocal rank fusion

Security

API keys authenticate all requests via Authorization: Bearer header
Each API key is scoped to the user's owned and purchased collections
Cross-tenant data access is impossible — all queries are filtered by accessible collection IDs
API keys should never be committed to version control

Troubleshooting

Issue	Solution
"Tool not found"	Restart your AI app after config changes. Verify your API key starts with `sk_live_`
"Unauthorized"	Check the `Authorization: Bearer` header format. Verify the key hasn't expired
No results	Ensure documents are uploaded and processing is complete. Try broader queries
Connection timeout	Check internet access. Verify server status at `https://mcp.ragora.app/health`

License

MIT

Ragora