Parse
About
Look up how any brand surfaces in ChatGPT and Google AI Overviews. Brands, prompts, sources, niches. Read-only.
Details
- Author
- parsegl
- Categories
- Marketing, Other
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Setup
Install Parse in your MCP client (Claude Desktop, Cursor, Windsurf, and others).
Repository: https://github.com/parsegl/parse-mcp
Follow the installation instructions in the repository README, then restart your MCP client.
Improve AI visibility research with Parse. Find how brands appear across AI-search prompts, citation sources, niches, and competitors, then turn that data into marketer-ready actions. Use the server to discover relevant brands, audit a brand's visibility profile, compare competitors, inspect high-intent prompts, identify source opportunities, and build 30-day visibility plans. Parse returns concise research briefs, fetchable result IDs, public score summaries, top prompts, top citation domains, related products, and dataset freshness signals so marketers can move from raw AI visibility data to prioritized SEO, content, PR, and listing work.
Hosted MCP endpoint:https://mcp.parse.gl/mcp
The easiest install path is the published npm shim:
That command starts a local stdio bridge which proxies to the hosted Parse MCP server athttps://mcp.parse.gl/mcp.
For LLM/agent-focused setup notes, seellms-install.md.
- mcp-worker/: Cloudflare Worker source for the hosted Streamable HTTP MCP server.
- npm/:parse-gl-mcpnpm shim that runs the hosted server through package-localmcp-remote.
- mcp-bundle/: MCPB bundle metadata and node entry point.
- parse_search: Search brands, organic AI prompts, niches, and citation sources.
- parse_get_brand: Fetch a marketer-readable AI visibility brief for a brand.
- parse_get_prompt: Fetch one public organic prompt.
- parse_get_stats: Summarize public Parse dataset scale and freshness.
- searchandfetch: Compatibility aliases for clients that expect those names.
- parse://showcase-brands
- parse://niches
- parse://glossary
- compare-brands
- audit-my-brand
- industry-leaders
- source-opportunities
- prompt-set-planner
- ai-visibility-30-day-plan
{ "mcpServers": { "parse": { "command": "npx", "args": ["-y", "-p", "@parse-gl/mcp", "parse-mcp"] } } }
Clients that support hosted MCP endpoints directly can connect to:
{ "mcpServers": { "parse": { "transport": "http", "url": "https://mcp.parse.gl/mcp" } } }
cd npm npm ci npm test npx -y -p @parse-gl/mcp parse-mcp
cd mcp-worker npm ci npm test npm run typecheck
Copymcp-worker/wrangler.example.tomltomcp-worker/wrangler.tomland fill in your own Cloudflare account, route, and KV namespace IDs. Store secrets withwrangler secret put; do not commit them.
- WORKER_HASH_SALT
- CF_ORIGIN_VERIFY_SECRET, if your Parse origin requires it
- VERCEL_AUTOMATION_BYPASS_SECRET, if your Vercel project requires it
- MCP_INTERNAL_SECRET, if enabling the internal usage endpoint
- Raw IP addresses are hashed at the worker boundary before rate limiting or telemetry.
- User-Agent values are reduced to a client-family label before persistence.
- Origin validation is strict for browser clients; missing Origin is allowed for native MCP clients.
- Upstream verification and bypass secrets are sent only as HTTP headers.
- This public repository intentionally excludes.env,.wrangler,.claude, andnode_modules.
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