For AI Agents

Reflect ships three integration surfaces optimized for AI agents and the IDEs that host them:

llms.txt

The entire docs site as plain text. Fetch with curl or urllib, drop into Cursor @docs or any RAG indexer.

Skills

Agent skills installed via npx skills. The integrate-reflect skill walks a coding agent through adding Reflect to a project end-to-end.

MCP server

retrieve_memories and create_memory tools over the Model Context Protocol. Compatible with Cursor, Claude Code, Cline, Continue, Windsurf, Zed, and more.

llms.txt — docs as plain text

The docs site auto-generates two plain-text bundles for ingestion by AI agents:

URL	Purpose	Size
`/llms.txt`	Curated index with markdown links to every page	~2 KB
`/llms-full.txt`	Full docs site concatenated into one file	~50 KB

Both serve as text/plain.

Fetch with curl or urllib, not a JS-rendered HTML fetcher. The HTML console at reflect.starlight-search.com is a single-page app and won’t yield content to plain HTTP fetchers — the text bundles above are the right entry point for any agent.

curl -sS https://docs.starlight-search.com/llms-full.txt -o reflect-docs.txt

Wiring into IDEs

Cursor
Claude Code
Any agent

Add the URL via Cursor’s docs feature:

@docs add reflect https://docs.starlight-search.com/llms-full.txt

Then reference it in any chat with @reflect.

Mention the URL in your project’s CLAUDE.md or in a chat — Claude Code will fetch it on demand:

Reflect docs as plain text: https://docs.starlight-search.com/llms-full.txt

Fetch the file at startup and inject into the agent’s context:

import urllib.request

docs = urllib.request.urlopen(
    "https://docs.starlight-search.com/llms-full.txt"
).read().decode("utf-8")
# then add `docs` to your system prompt

Skills — installable workflow guides

Reflect publishes agent skills under StarlightSearch/reflect-skills on GitHub. Skills are installed with the skills CLI and work in Claude Code, Cursor, Codex, Gemini CLI, Antigravity, Deep Agents, Pi, Qwen Code, and other agent hosts.

`integrate-reflect`

Walks a coding agent through adding Reflect to a Python agent project end-to-end: SDK install, framework-specific loop placement, parameter tuning, LLM-as-judge wiring, and a mandatory smoke test that proves the loop closes. Covers OpenAI Agents SDK, Claude Agent SDK, LangGraph, Pydantic AI, and a generic-loop fallback. Handles both fresh projects (scaffolds a starter agent) and existing codebases (overlays Reflect onto existing loops). Install globally:

npx skills add StarlightSearch/reflect-skills@integrate-reflect -g -y

Triggers automatically when the user says:

“add Reflect to my agent”
“give my agent memory”
“build an agent with Reflect”
“wire up client.trace”
“ctx.memories is empty” / “q-values aren’t moving”

Browse the source and contribute on GitHub.

Reflect also has a project-level Skill API that distills your reviewed traces into a unified guide for your specific agent. That’s a different feature than the installable workflow skills here. The installable skills teach a coding agent how to integrate Reflect; the Skill API is what Reflect generates from your traces once you’re integrated.

MCP server

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

Quick connect — JSON-based clients

Most MCP-capable IDEs use the same JSON config block. Drop this into the right file for your client:

{
  "mcpServers": {
    "reflect": {
      "url": "https://api.starlight-search.com/mcp",
      "headers": {
        "Authorization": "Bearer rf_live_..."
      }
    }
  }
}

Client	Config file
Cursor	`.cursor/mcp.json` (project) or `~/.cursor/mcp.json` (global)
Cline (VS Code)	`cline_mcp_settings.json` (Cline → Settings → MCP Servers → Configure)
Continue (VS Code/JetBrains)	`~/.continue/config.json` under `experimental.modelContextProtocolServers`
Windsurf	`~/.codeium/windsurf/mcp_config.json`
Zed	`~/.config/zed/settings.json` under `"context_servers"` (no `mcpServers` wrapper)

Quick connect — Claude Code

claude mcp add --transport http reflect https://api.starlight-search.com/mcp \
  --header "Authorization: Bearer rf_live_..."

Stdio transport (alternative)

If your client doesn’t support HTTP MCP servers, run the local stdio version with uvx:

{
  "mcpServers": {
    "reflect": {
      "command": "uvx",
      "args": ["--from", "reflect-mcp-server", "reflect-mcp-server", "--transport", "stdio"],
      "env": {
        "REFLECT_API_KEY": "rf_live_...",
        "REFLECT_PROJECT_ID": "your-project-id",
        "REFLECT_API_URL": "https://api.starlight-search.com"
      }
    }
  }
}

For self-hosting, advanced options, and the full env-var reference, see the MCP server guide.

Quick reference

What you want	Where to go
Read all the docs in one fetch	`https://docs.starlight-search.com/llms-full.txt`
Browse the docs index	`https://docs.starlight-search.com/llms.txt`
Add Reflect to a Python agent project	`npx skills add StarlightSearch/reflect-skills@integrate-reflect`
Connect any MCP client to Reflect	`https://api.starlight-search.com/mcp` (Bearer auth)
Browse all skills	StarlightSearch/reflect-skills
Get a project + API key	Reflect console

Getting started

Core Concepts

Examples

Roadmap

llms.txt

Skills

MCP server

llms.txt — docs as plain text

Wiring into IDEs

Skills — installable workflow guides

`integrate-reflect`

MCP server

Quick connect — JSON-based clients

Quick connect — Claude Code

Stdio transport (alternative)

Quick reference

llms.txt

Skills

MCP server

​llms.txt — docs as plain text

​Wiring into IDEs

​Skills — installable workflow guides

​integrate-reflect

​MCP server

​Quick connect — JSON-based clients

​Quick connect — Claude Code

​Stdio transport (alternative)

​Quick reference

llms.txt — docs as plain text

Wiring into IDEs

Skills — installable workflow guides

`integrate-reflect`

MCP server

Quick connect — JSON-based clients

Quick connect — Claude Code

Stdio transport (alternative)

Quick reference