Socialcrawl MCP Server

Socialcrawl MCP Server is the official Model Context Protocol server for the SocialCrawl API. The direct product link points to https://socialcrawl.dev, while the repository https://github.com/socialcrawl/mcp contains source code, README, license, and setup guidance. According to the README, the server connects AI agents to a unified data API covering 48 platforms and 381 endpoints. Those sources include profiles, posts, comments, search results, trends, and analytics from platforms such as TikTok, Instagram, YouTube, Twitter/X, LinkedIn, Reddit, GitHub, and Hacker News, as well as commerce, review, app-store, travel, news, and web-research data. For Skill Road, this entry primarily closes the previously empty Social Media category.

Social listening rather than one-platform scraping

The value is not just automating one network. It is giving an agent a consistent tool layer across many public data sources. Teams can bring social listening, competitor monitoring, topic research, creator or community analysis, and early market observation into agentic workflows. An agent might search public posts, compare profiles, inspect comment patterns, or prepare trend comparisons across several sources. This does not replace an official analytics product from a platform, and it does not replace legal review, but it can make early research more structured and repeatable.

Setup and operating model

The README describes the server as the npm package socialcrawl-mcp, used from MCP clients such as Claude, Cursor, or other compatible hosts. Access requires a SocialCrawl API key. That key belongs in the intended environment or client configuration, not in prompts, public files, or committed repositories. Because many connected sources expose public but still sensitive context, teams should decide which platforms and endpoints are actually needed before enabling broad access. A narrow first trial should use a small set of sources and a clear research question rather than handing an agent a general instruction to explore everything.

Data quality, permissions, and limits

Social-media data is time-sensitive, incomplete, and governed by different platform rules. An agent should therefore treat results as research input, not final truth. Privacy, terms of service, and internal review matter especially for person profiles, comments, reputation, influencer analysis, or competitor monitoring. The API can provide context, but it does not decide whether a specific analysis is legally, ethically, or brand-safe. Production workflows should keep human review, explicit source attribution, and controlled publication in place.

License, GitHub stars, and fit

The repository is MIT licensed. The GitHub API reported exactly 12 stars for https://github.com/socialcrawl/mcp on 2026-09-07; that number is a snapshot of repository popularity, not a security or quality guarantee. Costs and usage limits depend on the SocialCrawl offering, API usage, platform coverage, and the selected AI client, so this public entry does not state fixed prices. Social Media, Research, and Data Analysis fit because the server makes public social and web data findable, comparable, and analyzable. For Skill Road, the entry is useful because it gives a previously empty user-facing category a clear, officially labeled MCP server.

MCP client, Node.js/npm, and SocialCrawl API access.

Configure the socialcrawl-mcp npm package in the MCP client and store the SocialCrawl API key securely as an environment variable.

npx socialcrawl-mcp

SocialCrawl API key per the provider.

Access depends on the API key, available endpoints, and SocialCrawl account.

Tool calls go to the SocialCrawl API and can return public social, web, review, and search data to the MCP client.

Broad platform queries, personal data, API keys in prompts, and unchecked downstream use can create privacy or compliance risks.