Echoloc MCP
Company technographics from hiring data: find companies adopting, replacing or evaluating technologies and enrich domains with firmographics and hiring signals.
Installation
Les étapes d'installation sont dans la documentation ci-dessous. Documentation
Documentation
Tirée du README du projet sur GitHub, actualisée chaque semaine. Les liens ouvrent GitHub.
Sommaire
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-Keyheader (also acceptsAuthorization: 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_evaluatingarrays 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.
Questions fréquentes
Qu'est-ce que Echoloc MCP ?
Company technographics from hiring data: find companies adopting, replacing or evaluating technologies and enrich domains with firmographics and hiring signals.
Comment installer Echoloc MCP ?
Suivez les étapes d'installation de sa documentation, affichée sur cette page et dans son dépôt.
Echoloc MCP est-il open source ?
Oui. Son code est sur GitHub sous licence MIT.
Qui maintient Echoloc MCP ?
Il est publié par echoloc-ai. AI.tn le référence sans le maintenir ni le recommander.
Issu des listes communautaires awesome-mcp-servers et du dépôt GitHub du projet. Être listé n'est pas une recommandation : vérifiez le code et les permissions d'un serveur avant de lui donner accès à vos données.