Kanto Labs

Web data, SEO, domain, company, trends, OCR, document and image tools for AI assistants via Apify.

What does this entry provide?

Kanto Labs is an MCP server entry in ChatHome Skills, sourced from Official MCP Registry and scored 51/100. As a Model Context Protocol server, it exposes tools that MCP-compatible LLM clients such as Claude, Cursor, and Copilot can call directly, extending an agent's reach beyond its built-in capabilities. ChatHome Skills discovered this entry through its daily ingest of official registries and GitHub discovery queries, and re-verifies repository facts, freshness signals, and install metadata on every run. The quality score weighs official-registry presence, a working install command, license clarity, GitHub star trajectory, and repository freshness — the full formula is on the Sources page. No automated install command is listed; check the repository for manual setup instructions. Review the last-pushed date and repository status before adding Kanto Labs to a production agent workflow; the snapshot facts below are point-in-time values from the most recent ingest.

Snapshot facts

Source: Official MCP Registry
Quality: 51/100
Install method: manual
Repo: kanto-labs/kanto-labs-mcp
Repo updated: Sep 23, 2026

Install command

See source docs

Install method: manual

Review the upstream source before running this command.

GitHub project Homepage

Quality

Repo stars

Repo updated

Sep 23, 2026

How is this score calculated?

Weighted across six dimensions, scored 0-100.
Provenance (25): listed in an official or curated registry.
Installability (25): a runnable install command beats a declared transport, which beats a source checkout.
Maintenance (20): recency of the last push; archived entries score zero here.
Adoption (20): repository stars on a log curve.
Documentation (10) and description quality (10): parsed manifest or SKILL.md frontmatter, and a real description rather than a placeholder.

MCP manifest

{
  "_meta": {
    "io.modelcontextprotocol.registry/official": {
      "status": "active",
      "isLatest": true,
      "updatedAt": "2026-09-23T04:05:02.217246Z",
      "publishedAt": "2026-09-23T04:05:02.217246Z",
      "statusChangedAt": "2026-09-23T04:05:02.217246Z"
    }
  },
  "server": {
    "name": "io.github.Akhiyugo/kanto-labs-mcp",
    "title": "Kanto Labs",
    "$schema": "https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json",
    "version": "1.2.0",
    "packages": [
      {
        "transport": {
          "type": "stdio"
        },
        "fileSha256": "62c70be545f2dd14a992d5a285be8ea7a1db7cdb37b2a74345ec20d7d47568a8",
        "identifier": "https://github.com/kanto-labs/kanto-labs-mcp/releases/download/v1.2.0/kanto-labs-mcp.mcpb",
        "registryType": "mcpb",
        "environmentVariables": [
          {
            "name": "APIFY_TOKEN",
            "isSecret": true,
            "isRequired": true,
            "description": "Your Apify API token (console.apify.com/settings/integrations). Actor runs are billed to this account."
          },
          {
            "name": "KANTO_MAX_CHARGE_USD",
            "format": "number",
            "description": "Default spending cap per tool call in USD, enforced by Apify (default 1.00)."
          }
        ]
      }
    ],
    "repository": {
      "url": "https://github.com/kanto-labs/kanto-labs-mcp",
      "source": "github"
    },
    "websiteUrl": "https://apify.com/kantolabs",
    "description": "Web data, SEO, domain, company, trends, OCR, document and image tools for AI assistants via Apify."
  }
}

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