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
Tool | What it does |
| Find companies using given technologies (match |
| Resolve a domain (e.g. |
| 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.
Related MCP server: enrich-company-mcp
claude mcp add --transport http echoloc https://api.echoloc.ai/mcp \
--header "X-API-Key: YOUR_API_KEY"{
"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?
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-mcpcurl 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}}}'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.
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
Questions, production keys (higher limits, bulk feeds, licensing): hello@echoloc.ai — we reply within one business day.
Resolve a company domain (e.g. 'walgreens.com') to its full profile: firmographics, hiring stats, and the technology stack with adoption context (using / adopting / replacing / evaluating).
Inputs: domain (required).
Catalog of all technologies in the dataset with per-technology company counts. sort='count' (most used first) or 'name'.
Inputs: page, sort, page_size.
Find companies using the given technologies, ranked by usage. Names are case-insensitive ('snowflake' == 'Snowflake'); 10,000+ technologies are tracked (use list_technologies to explore). match='any' needs at least one technology, 'all' needs every one.
Inputs: technologies (required), page, match, page_size.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
Scored across 3 tools
Each tool serves a distinct purpose: searching companies by tech, retrieving a specific company's profile, and listing technologies. There is no overlap or ambiguity.
All tool names follow a consistent verb_noun pattern (search_companies_by_technologies, get_company_by_domain, list_technologies). Naming is clear and predictable.
With 3 tools, the server is tightly scoped to its domain (company tech intelligence). Each tool is essential and covers the core functionality without bloat.
The tools enable searching, retrieving details, and exploring the technology catalog. Minor gaps exist (e.g. no direct company search by name), but the set covers the primary workflows well.
Your agent needs to know what a site is built on and who owns it — or to find every site running a given technology. **What you can ask for** • "What is this site built on — CMS, analytics, payments, CDN?" • "Find every domain running Shopify in Germany." • "Who owns this domain, and when does it expire?" • "How many sites use this technology, and is that growing?" • "Find domains whose HTML contains this snippet." **How to use it** Point any MCP client at https://mcp.aisa.one/seo-domains/mcp and sign in with OAuth — there is no key to create or paste. 12 tools: technology detection for one domain, domains by technology, domains by HTML term, technology stats and aggregations, plus whois overview and its filters. **Why this rather than the source** Prospecting by tech stack and ownership lookup in the same call shape. **It is also a door to the rest** The same login reaches 26 sources and 580+ operations. Find the stack here, then ask the same agent for that company's traffic and the people to contact — without adding a second server. **What it costs** Finding and inspecting an operation is free. Running one is billed per call at API prices, with no seat and no monthly minimum, and every call takes max_price_usd so an agent cannot overspend by accident. **Where else it reaches** https://mcp.aisa.one/sales/mcp turns a technology list into a contactable pipeline. https://mcp.aisa.one/seo/mcp for all of it at once — rankings, keywords, backlinks, site health and AI-answer visibility across DataForSEO, Semrush and Ahrefs.
Search 760K+ companies by technographics with direction of change: adopting, replacing, evaluating
Public company research with 9 focused tools: technology, hiring intent, open jobs, job changes, Google Ads and published contacts. Get a qualifying four-signal company profile for $0.03, plus breakout_summary growth estimates. Start with the free labeled example.com sandbox, 10 free successful calls per agent per UTC day (subject to a shared network ceiling), or an eligible 25-call trial. Setup: https://gethirepulse.xyz/?ref=glama-b2b#start-b2b . Reconnect to https://gethirepulse.xyz/mcp for all 27 tools, including batch and footprint research. Growth signals are estimates.
The Google for AI agents — company intel, competitor tracking, market research via MCP. JSON output
