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echoloc-ai/echoloc-mcp

echoloc-ai/echoloc-mcp

Company technographics from
在 GitHub 查看 ↗直链 · 无中转页
配置模板(请按你的客户端调整)
claude mcp add echoloc-mcp -- npx -y echoloc-mcp
这是根据仓库名生成的可粘贴骨架,命令行参数与包名请以该项目 README 为准。
★ 数取值
0 ★ · echoloc-ai/echoloc-mcp · 取自 GitHub 搜索 API · (2026-10-16 20:00:20 核对)
来源明细
收录自 punkpeye/awesome-mcp-servers 榜单(我们从中收集的条目之一) · 条目类型:MCP 服务
收录与活跃
收录于 2026-10-09 · 最近见到 2026-10-16 · 共见到 32 次 · 被 7 个来源列出
评分构成
综合分 703 · 7 个来源 · mcp
常见问题(答案都来自我们的记录)
怎么安装?
我们【没有】从该仓库取到安装命令(我们的 install 覆盖率只有约 4%)。请看它的 README 或 releases 页。
它适合谁 / 用来做什么?
我们把它归在这些标签下: MCP 服务。标签来自条目自身,不是我们强加的分类。
谁维护它、还在更新吗?
仓库 echoloc-ai/echoloc-mcp;我们收录于 2026-10-09;最近见到 2026-10-16。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。
第三方质量标记

echoloc MCP server — company technographics for AI agents

以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

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
Cursor / any MCP client
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:
Or via Docker:
Raw JSON-RPC example
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+
来源
awesome · https://github.com/echoloc-ai/echoloc-mcp
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