This is a hosted MCP server that connects your AI assistant to Ragora's knowledge base platform via streamable HTTP. You point your client at their cloud endpoint with a Bearer token, no local setup required. It exposes three core tools: discover_collections to see what knowledge bases you have access to, search to query across all of them at once, and search_collection to narrow down by name with optional tag and metadata filters. Ragora also generates dedicated tools per collection like search_employee_handbook or get_topic_product_docs. Under the hood it runs hybrid search combining dense vectors and BM25. Reach for this when you want RAG over your own document collections without running infrastructure yourself.
Public tool metadata for what this MCP can expose to an agent.
discover_collectionsDiscover all knowledge bases you have access to. Returns collection names, descriptions, content types, stats, available operations, and usage examples for each collection. Call this first to understand what data is available before searching.Discover all knowledge bases you have access to. Returns collection names, descriptions, content types, stats, available operations, and usage examples for each collection. Call this first to understand what data is available before searching.
No parameter schema in public metadata yet.
searchSearch across ALL your knowledge bases at once. Use this when you want broad results or aren't sure which collection has the answer. For targeted search in a specific collection, use search_collection() instead. Args: query: Natural language search query. top_k: Maximum number...2 paramsSearch across ALL your knowledge bases at once. Use this when you want broad results or aren't sure which collection has the answer. For targeted search in a specific collection, use search_collection() instead. Args: query: Natural language search query. top_k: Maximum number...
querystringtop_kintegersearch_collectionSearch a specific knowledge base by name. Use discover_collections() first to find available collection names. Args: collection_name: Human-readable collection name or slug (e.g. "employee_handbook"). query: Natural language search query. top_k: Maximum number of results to re...5 paramsSearch a specific knowledge base by name. Use discover_collections() first to find available collection names. Args: collection_name: Human-readable collection name or slug (e.g. "employee_handbook"). query: Natural language search query. top_k: Maximum number of results to re...
querystringtop_kintegerfiltersvaluecustom_tagsvaluecollection_namestringcheck_balanceCheck your current credit balance. Returns your remaining balance and estimated USD value.Check your current credit balance. Returns your remaining balance and estimated USD value.
No parameter schema in public metadata yet.
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
Sign up at ragora.app and create an API key at Settings > API Keys.
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 mcp add --transport http ragora https://mcp.ragora.app/mcp \
--header "Authorization: Bearer sk_live_your_key_here"
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"
}
}
}
}
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"
}
}
}
}
Add to ~/.codeium/windsurf/mcp_config.json:
{
"mcpServers": {
"ragora": {
"serverUrl": "https://mcp.ragora.app/mcp",
"headers": {
"Authorization": "Bearer sk_live_your_key_here"
}
}
}
}
Ragora uses Streamable HTTP transport. Point any MCP-compatible client to:
https://mcp.ragora.app/mcpPOSTAuthorization: Bearer sk_live_your_key_here| 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 |
search(query, top_k?)
query (required): Natural language search querytop_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 querytop_k (optional): Number of results (default: 5)custom_tags (optional): Tags to scope retrievalfilters (optional): Metadata filtersFor each collection you have access to, dedicated tools are generated using the collection's slug:
search_{slug} — semantic search with optional version, tags, and filtersget_topic_{slug} — retrieve information about a specific topiclist_versions_{slug} — list available documentation versionsFor example, a collection called "Employee Handbook" gets:
search_employee_handbookget_topic_employee_handbooklist_versions_employee_handbookConfigure tool names and descriptions in the Ragora dashboard under Collection > MCP Settings.
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?"
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)
Authorization: Bearer header| 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 |
MIT
io.github.ericm1018/skillfm-llm-cost-optimizer-openai-anthropic-usage
io.github.mikerawsonnz/llm-orchestration-agent
io.github.mikerawsonnz/authenticated-llm-agent
labforgedev/copilot-memory-mcp
csoai-org/agent-prompt-injection-firewall-mcp
io.github.mikerawsonnz/authenticated-multi-llm-agent