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extract_gov_landscape

Read-only

Analyze government tech contractors by querying federal contracts, GitHub activity, Hacker News discussions, and product changelogs to assess market position, development pace, and developer community awareness.

Instructions

Composite government intelligence tool. Given a company name, keyword, or NAICS code, simultaneously queries: (1) USASpending.gov for federal contract awards, (2) GitHub for the company's repo activity, (3) Hacker News for developer community awareness, and (4) their product changelog for release velocity. Answers: Who is winning government contracts in this space? Are they actually building? Does the dev community know about them? Returns a unified 4-source timestamped report. Unique — not available in any other MCP server.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesCompany name (e.g. 'Palantir'), keyword (e.g. 'artificial intelligence'), or NAICS code (e.g. '541511'). For GitHub and changelog sections, also optionally provide a GitHub URL.
github_urlNoOptional GitHub repo URL for the company (e.g. 'https://github.com/palantir/palantir-java-format'). If omitted, GitHub and changelog sections use the query as a search term.
max_lengthNo

Implementation Reference

  • The handler function for 'extract_gov_landscape' which aggregates data from USASpending, Hacker News, GitHub, and a Changelog adapter.
    async ({ query, github_url, max_length }) => {
      const perSection = Math.floor((max_length ?? 12000) / 4);
    
      // All four sources fire in parallel — if one fails the others still return
      const [contractsResult, hnResult, repoResult, changelogResult] = await Promise.allSettled([
        // 1. The anchor: who is actually winning federal money in this space
        govContractsAdapter({ url: query, maxLength: perSection }),
        // 2. Dev community signal: does anyone in tech know about these companies
        hackerNewsAdapter({
          url: `https://hn.algolia.com/api/v1/search?query=${encodeURIComponent(query)}&tags=story&hitsPerPage=10`,
          maxLength: perSection,
        }),
        // 3. GitHub activity: are they actually building, or contract farmers
        repoSearchAdapter({ url: github_url ?? query, maxLength: perSection }),
        // 4. Release velocity: how fast are they shipping product
        changelogAdapter({ url: github_url ?? query, maxLength: perSection }),
      ]);
    
      const section = (
        label: string,
        result: PromiseSettledResult<{ raw: string; content_date: string | null; freshness_confidence: string }>
      ) =>
        result.status === "fulfilled"
          ? `## ${label}\n${result.value.raw}`
          : `## ${label}\n[Unavailable: ${(result as PromiseRejectedResult).reason}]`;
    
      const combined = [
        `# Government Intelligence Landscape: "${query}"`,
        `Generated: ${new Date().toISOString()}`,
        `Sources: USASpending.gov · Hacker News · GitHub · Changelog`,
        "",
        section("🏛️ Federal Contract Awards (USASpending.gov)", contractsResult),
        section("💬 Developer Community Awareness (Hacker News)", hnResult),
        section("📦 GitHub Repository Activity", repoResult),
        section("🔄 Product Release Velocity (Changelog)", changelogResult),
      ].join("\n\n");
    
      return { content: [{ type: "text", text: combined }] };
    }
  • src/server.ts:296-311 (registration)
    Registration of the 'extract_gov_landscape' tool including description and input schema.
    server.registerTool(
      "extract_gov_landscape",
      {
        description:
          "Composite government intelligence tool. Given a company name, keyword, or NAICS code, simultaneously queries: (1) USASpending.gov for federal contract awards, (2) GitHub for the company's repo activity, (3) Hacker News for developer community awareness, and (4) their product changelog for release velocity. Answers: Who is winning government contracts in this space? Are they actually building? Does the dev community know about them? Returns a unified 4-source timestamped report. Unique — not available in any other MCP server.",
        inputSchema: z.object({
          query: z.string().describe(
            "Company name (e.g. 'Palantir'), keyword (e.g. 'artificial intelligence'), or NAICS code (e.g. '541511'). For GitHub and changelog sections, also optionally provide a GitHub URL."
          ),
          github_url: z.string().optional().describe(
            "Optional GitHub repo URL for the company (e.g. 'https://github.com/palantir/palantir-java-format'). If omitted, GitHub and changelog sections use the query as a search term."
          ),
          max_length: z.number().optional().default(12000),
        }),
        annotations: { readOnlyHint: true, openWorldHint: true },
      },
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description adds valuable behavioral context beyond annotations. While annotations indicate read-only and open-world operations, the description reveals this is a composite tool that queries four sources simultaneously, returns a unified timestamped report, and has specific output format expectations (answers three questions). It doesn't mention rate limits, authentication needs, or data freshness, but provides meaningful operational context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficiently structured and front-loaded: it immediately states this is a composite tool, lists the four sources, specifies the three questions it answers, and describes the output format. Every sentence adds value without redundancy. The final sentence about uniqueness appropriately emphasizes differentiation without being verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (composite queries across four sources) and lack of output schema, the description does well to specify what questions it answers and the report format. However, it doesn't detail potential limitations (like data availability across sources) or error handling. With annotations covering safety aspects and good schema coverage, the description provides solid context but could be more complete about operational constraints.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 67% schema description coverage, the description doesn't add significant parameter semantics beyond what the schema provides. The schema already documents the three parameters well, including the optional github_url and default max_length. The description mentions using the query for GitHub/changelog sections when github_url is omitted, but this is already implied in the schema descriptions. Baseline 3 is appropriate given the good schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states the tool's purpose: it's a composite intelligence tool that simultaneously queries four specific sources (USASpending.gov, GitHub, Hacker News, product changelog) to answer three specific questions about government contract winners, development activity, and developer community awareness. It clearly distinguishes itself from siblings by being 'Unique — not available in any other MCP server' and by combining these four sources into one unified report.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context about when to use this tool: for analyzing companies/keywords/NAICS codes across government contracts, development activity, and community awareness. It implicitly distinguishes from siblings by being a composite tool, but doesn't explicitly state when NOT to use it or name specific alternatives among the sibling tools (like extract_govcontracts, extract_github, extract_hackernews).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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