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osint-mcp-server

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wayback_snapshots

Retrieve historical snapshots of web pages from the Wayback Machine to analyze URL changes, view archived content, and track website evolution over time.

Instructions

Get Wayback Machine snapshot history for a specific URL. Returns timestamps, status codes, and direct archive links. Shows first/last seen dates.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesURL to get snapshot history for
limitNoMaximum snapshots to return (default: 100)

Implementation Reference

  • The logic for fetching wayback snapshots from the Wayback Machine API.
    export async function waybackSnapshots(url: string, limit = 100): Promise<WaybackSnapshotsResult> {
      await limiter.acquire();
    
      const params = new URLSearchParams({
        url,
        output: "json",
        fl: "timestamp,original,statuscode,mimetype",
        limit: String(limit),
      });
    
      const controller = new AbortController();
      const timeout = setTimeout(() => controller.abort(), 30000);
    
      try {
        const res = await fetch(`https://web.archive.org/cdx/search/cdx?${params}`, { signal: controller.signal });
        if (!res.ok) throw new Error(`Wayback CDX returned ${res.status}`);
    
        const data: string[][] = await res.json();
        const rows = data.slice(1);
    
        const snapshots: WaybackSnapshot[] = rows.map((row) => ({
          timestamp: row[0] ?? "",
          url: row[1] ?? "",
          statusCode: row[2] ?? "",
          mimeType: row[3] ?? "",
          archiveUrl: `https://web.archive.org/web/${row[0]}/${row[1]}`,
        }));
    
        const firstSeen = snapshots.length > 0 ? snapshots[0].timestamp : undefined;
        const lastSeen = snapshots.length > 0 ? snapshots[snapshots.length - 1].timestamp : undefined;
    
        return { url, totalSnapshots: snapshots.length, firstSeen, lastSeen, snapshots };
      } finally {
        clearTimeout(timeout);
      }
    }
  • Data types for the wayback snapshot results.
    interface WaybackSnapshot {
      timestamp: string;
      url: string;
      statusCode: string;
      mimeType: string;
      archiveUrl: string;
    }
    
    interface WaybackSnapshotsResult {
      url: string;
      totalSnapshots: number;
      firstSeen?: string;
      lastSeen?: string;
      snapshots: WaybackSnapshot[];
    }
  • Tool registration and definition for wayback_snapshots.
    const waybackSnapshotsTool: ToolDef = {
      name: "wayback_snapshots",
      description: "Get Wayback Machine snapshot history for a specific URL. Returns timestamps, status codes, and direct archive links. Shows first/last seen dates.",
      schema: {
        url: z.string().describe("URL to get snapshot history for"),
        limit: z.number().optional().describe("Maximum snapshots to return (default: 100)"),
      },
      execute: async (args) =>
        json(await waybackSnapshots(args.url as string, args.limit as number | undefined)),
    };
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions what data is returned (timestamps, status codes, archive links, first/last seen dates) but doesn't cover important behavioral aspects like rate limits, authentication requirements, error conditions, pagination behavior (beyond the limit parameter), or whether this is a read-only operation.

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 perfectly concise with three clear sentences that each add value. The first sentence states the core purpose, the second describes the return data, and the third adds important context about first/last seen dates. No wasted words or redundant information.

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

Completeness3/5

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

For a read-only query tool with 100% schema coverage but no output schema, the description provides adequate but incomplete context. It covers what the tool does and what data it returns, but lacks information about behavioral constraints, error handling, and output format details that would be helpful for an AI agent to use it effectively.

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?

Schema description coverage is 100%, so the schema already documents both parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema. It mentions 'snapshot history' which aligns with the url parameter purpose, but provides no additional semantic context about parameter usage or constraints.

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 clearly states the tool's purpose with specific verbs ('Get', 'Returns', 'Shows') and resources ('Wayback Machine snapshot history for a specific URL'). It distinguishes from sibling tools by focusing on snapshot history rather than URL discovery (wayback_urls) or other OSINT functions.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. While it implicitly suggests usage for retrieving historical snapshots, it doesn't mention when not to use it or what other tools might be better for related tasks like finding available URLs (wayback_urls) or other historical data sources.

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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