echoloc MCP server — company technographics for AI agents

Remote Model Context Protocol server for the echoloc company-intelligence dataset: search 760,000+ companies by the technologies they use — with direction of change (what each company is adopting, replacing, and evaluating), hiring signals, and firmographics. Signals are extracted from millions of public job posts, so the data covers backend, data, cloud, and AI tooling that never appears in website source.

• Endpoint: https://api.echoloc.ai/mcp (Streamable HTTP, stateless)
• Registry name: ai.echoloc/company-technographics
• Auth: X-API-Key header (also accepts Authorization: Bearer)
• Free key: 100 requests/month, instant — sign up and copy it from echoloc.ai/app/api

Tools

Tool	What it does
search_companies_by_technologies	Find companies using given technologies (match any/all), ranked by usage. Case-insensitive, 10,000+ technologies tracked.
get_company_by_domain	Resolve a domain (e.g. walgreens.com) to a full profile: firmographics, hiring stats, tech stack with adoption context.
list_technologies	The full technology catalog with per-technology company counts.

All tools are read-only (readOnlyHint: true). Discovery (initialize, tools/list) requires no key; tool calls consume 1 credit each.

Quick start

Claude Code

claude mcp add --transport http echoloc https://api.echoloc.ai/mcp \
  --header "X-API-Key: YOUR_API_KEY"

Cursor / any MCP client

{
  "mcpServers": {
    "echoloc": {
      "url": "https://api.echoloc.ai/mcp",
      "headers": { "X-API-Key": "YOUR_API_KEY" }
    }
  }
}

Then ask things like:

Which financial-services companies are adopting Snowflake right now?

Pull the tech stack and hiring signals for walgreens.com.

Which companies are actively replacing VMware?

stdio bridge (Claude Desktop, local runners)

For stdio-only MCP clients this repo ships a dependency-free bridge (mcp_stdio_bridge.py) that forwards JSON-RPC to the hosted server:

{
  "mcpServers": {
    "echoloc": {
      "command": "python3",
      "args": ["/path/to/mcp_stdio_bridge.py"],
      "env": { "ECHOLOC_API_KEY": "YOUR_API_KEY" }
    }
  }
}

Or via Docker:

docker build -t echoloc-mcp .
docker run -i --rm -e ECHOLOC_API_KEY=YOUR_API_KEY echoloc-mcp

Raw JSON-RPC example

curl https://api.echoloc.ai/mcp \
  -H "Content-Type: application/json" \
  -H "X-API-Key: YOUR_API_KEY" \
  -d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"search_companies_by_technologies","arguments":{"technologies":["Snowflake"],"match":"any","page_size":10}}}'

What makes the data different

Most technographics are scraped from website source and can only see frontend tools. echoloc reads what companies say in their own hiring:

• Direction of change — tech_adopting, tech_replacing, tech_evaluating arrays on every profile, not just a static "uses X" flag.
• Hiring context — active jobs, hiring velocity, departments, leadership hires.
• Depth — 360,000+ companies with detected stacks across 10,000+ technologies, refreshed daily.

Links

• Agent fast lane: echoloc.ai/for-agents
• REST API docs: echoloc.ai/developers · OpenAPI spec
• LLM-readable summary: llms.txt · llms-full.txt
• Methodology: echoloc.ai/methodology
• Research built on this dataset: echoloc.ai/research

Support

Questions, production keys (higher limits, bulk feeds, licensing): hello@echoloc.ai — we reply within one business day.