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Tech Ecosystem Analysis MCP Server

@apifyforge

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基本情報

カテゴリ

その他

ライセンス

MIT

認証方式

oauth

作者

apifyforge

Tech Ecosystem Analysis MCP Server について

Tech ecosystem analysis for AI agents and LLM workflows — maps technology relationships, tracks adoption curves, detects CVE vulnerabilities, and scores tech stack risk across 6 live data sources.

Tech Ecosystem Analysis MCP Server の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "tech-ecosystem-analysis-mcp": {
      "url": "https://ryanclinton--tech-ecosystem-analysis-mcp.apify.actor/mcp"
    }
  }
}

Tech Ecosystem Analysis MCP Server のツール

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概要

What is Tech Ecosystem Analysis?

Tech Ecosystem Analysis is an MCP (Model Context Protocol) server for AI agents and LLM workflows that maps technology relationships, tracks adoption curves, detects CVE vulnerabilities, and scores tech stack risk from six live data sources. It is intended for engineering teams, security analysts, and CTOs evaluating frameworks, languages, or tools with structured, data-driven intelligence.

How to use Tech Ecosystem Analysis?

Add the server’s URL and optionally an Authorization header (Apify token) to your MCP client configuration (Claude Desktop, Cursor, Windsurf). The server exposes 8 tools that can be called directly from an AI agent with a single tool invocation; example HTTP and Python usage are provided in the README.

Key features of Tech Ecosystem Analysis

  • 8 MCP tools covering vulnerability, adoption, sentiment, and risk scoring
  • Live data from GitHub, NVD, StackExchange, Hacker News, Wikipedia, and Tech Stack Detector
  • Parallel execution of up to 6 actor calls per tool invocation
  • Structured JSON output with scores, classifications, and recommendations
  • Streamable HTTP transport – no SSE configuration required
  • Apify platform features: scheduling, API access, spending limits, and integrations

Use cases of Tech Ecosystem Analysis

  • Engineering teams comparing framework risk before committing resources
  • Security engineers mapping CVEs and prioritizing remediation
  • VC and M&A analysts assessing technology moat and liability
  • DevRel teams identifying growing frameworks for content investment
  • AI agents monitoring production stack for new vulnerabilities weekly

よくある質問

1

What tools does Tech Ecosystem Analysis expose?

It provides 8 tools: `map_tech_ecosystem`, `assess_tech_adoption`, `detect_tech_vulnerabilities`, `analyze_developer_sentiment`, `score_tech_stack_risk`, `track_framework_trends`, `assess_tech_maturity`, and `generate_tech_report`. Each tool returns specific structured data.

2

What data sources are used?

The server queries GitHub Search, NVD CVE Database, StackExchange, Hacker News, Wikipedia, and the Tech Stack Detector (for live URL scanning). All data is fetched at query time, not from a cached snapshot.

3

How are the scoring algorithms computed?

Scores are 0–100 composites. For example, the Vulnerability Exposure Score uses weighted severity (critical×3, high×2, other×1), capped at 100. The Tech Stack Risk Score combines CVE exposure (40%), inverse community support (35%), and inverse maturity (25%). Full formulas are documented.

4

Do I need an Apify account and token?

Yes. The server runs on the Apify platform. You must provide an Apify API token in the `Authorization` header when connecting. A free or paid Apify account is required to generate a token.

5

What transport does the server use?

It uses Streamable HTTP transport – no SSE (Server-Sent Events) configuration needed. The endpoint accepts standard HTTP POST requests.

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