Skip to main content
The Reflect MCP server exposes two tools — retrieve_memories and create_memory — over the Model Context Protocol. Connect it to any MCP-capable agent or IDE and your AI assistant will automatically query past lessons before hard tasks and record new ones after each run. MCP endpoint: https://api.starlight-search.com/mcp
Auth: Authorization: Bearer <your-api-key>
Transport: Streamable HTTP Get your API key from the Reflect console.

​
Claude Code

Add the server to your project or global config: 
claude mcp add --transport http reflect https://api.starlight-search.com/mcp \
  --header "Authorization: Bearer rf_live_..."
Or add it manually to .claude/settings.json (project) or ~/.claude/settings.json (global): 
{
  "mcpServers": {
    "reflect": {
      "type": "http",
      "url": "https://api.starlight-search.com/mcp",
      "headers": {
        "Authorization": "Bearer rf_live_..."
      }
    }
  }
}
Verify it loaded: 
claude mcp list

​
Cursor

Open Settings → MCP (or ~/.cursor/mcp.json) and add: 
{
  "mcpServers": {
    "reflect": {
      "type": "http",
      "url": "https://api.starlight-search.com/mcp",
      "headers": {
        "Authorization": "Bearer rf_live_..."
      }
    }
  }
}
Restart Cursor. The tools appear in Agent mode automatically.

​
Windsurf

Open Settings → Cascade → MCP Servers and add a new server: 
{
  "reflect": {
    "serverUrl": "https://api.starlight-search.com/mcp",
    "headers": {
      "Authorization": "Bearer rf_live_..."
    }
  }
}

​
Cline / Continue / other MCP clients

Any client that supports streamable HTTP transport uses the same config pattern: 
{
  "mcpServers": {
    "reflect": {
      "type": "http",
      "url": "https://api.starlight-search.com/mcp",
      "headers": {
        "Authorization": "Bearer rf_live_..."
      }
    }
  }
}

​
Per-project scoping with X-Project-Id

By default the server uses the project ID configured on your API key. To scope memories to a specific project per-request, pass the X-Project-Id header: 
{
  "headers": {
    "Authorization": "Bearer rf_live_...",
    "X-Project-Id": "my-project"
  }
}

​
Available tools

​
retrieve_memories

Search the memory store for lessons from prior tasks. Call this before starting non-trivial work.
ParameterTypeDefaultDescription
querystringrequiredNatural-language description of the task you are about to do
limitint5Max memories to return (up to 20)
lambda_float0.5Blend between semantic similarity (1.0) and Q-value / learned utility (0.0)
Returns a list of memories with id, task, reflection, q_value, similarity, score, and success. Save the memory_ids — you’ll pass them to create_memory.

​
create_memory

Persist a completed run as a memory so the agent can learn from it. Call this after the user confirms success or gives corrective feedback.
ParameterTypeDefaultDescription
taskstringrequiredThe task the agent was executing
final_responsestringrequiredThe agent’s final answer or deliverable
trajectorystring or listrequiredTool calls, decisions, and errors that led to the answer
result"pass" or "fail"requiredOutcome — drives the reward signal
feedback_textstringoptionalVerbatim or summarized user feedback
retrieved_memory_idslist[string]optionalIDs from retrieve_memories — enables Q-value updates

​
Verify the connection

The health endpoint requires no auth: 
curl https://api.starlight-search.com/mcp/health
# {"status": "ok"}