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  3. InsightSocial
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Health: ActiveRecent health check succeeded.Last checked 10/13/2026, 10:01:59 PM

InsightSocial

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social-mediapublic-dataanalyticsmcp

Access live public data from 25 social platforms through one MCP interface and a unified response schema.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag β€” we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON β–Ύ

Client Config & Setup

Configure Environment Variables (API Keys, Tokens, Options):
Add required secrets below β€” values are included directly in the generated snippet so you can copy and paste with confidence.
Quick Add:
Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "insightsocial": {
      "command": "npx",
      "args": [
        "-y",
        "insightsocial"
      ],
      "env": {
        "INSIGHTSOCIAL_API_KEY": "YOUR_VALUE_HERE",
        "INSIGHTSOCIAL_BASE_URL": "YOUR_VALUE_HERE",
        "INSIGHTSOCIAL_HOME": "YOUR_VALUE_HERE"
      }
    }
  }
}

πŸ’‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing Alternatives🌐 More in Social Media

Overview

InsightSocial MCP server gives AI agents access to live public data from 25 social platforms through the InsightSocial API. It provides endpoint discovery, endpoint descriptions, data retrieval, saved-result inspection, and credit lookup through MCP tools, with a unified schema across platforms. Use it when an agent needs profiles, posts, comments, engagement, searches, transcripts, jobs, ads, products, or local business listings from supported networks. It runs locally over stdio or can be accessed through the hosted MCP endpoint.

Use cases

β€’Search public profiles and content across social platforms
β€’Compare engagement fields across networks
β€’Retrieve transcripts, comments, followers, or hashtags
β€’Inspect saved API responses without making another call
β€’Check endpoint prices and account credit usage

Key features

β€’Access to 25 social platforms
β€’More than 300 searchable API endpoints
β€’Unified schema across supported networks
β€’Full response saving with local jq reshaping
β€’Endpoint pricing and dry-run quotes
β€’Local stdio and hosted MCP access

Capabilities & Tool Schemas

Inspect callable tools, capabilities, and parameters exposed to AI agents by InsightSocial.

Extracted Tool Capabilities
Access to 25 social platforms
More than 300 searchable API endpoints
Unified schema across supported networks
Full response saving with local jq reshaping
Endpoint pricing and dry-run quotes
Local stdio and hosted MCP access

How InsightSocial works

What InsightSocial does

The InsightSocial MCP server exposes the InsightSocial API to AI agents. The API covers 25 platforms, including Instagram, TikTok, LinkedIn, Facebook, YouTube, X, Reddit, Threads, Pinterest, Bluesky, Truth Social, Snapchat, Telegram, Twitch, Kick, Rumble, Kwai, Douyin, Xiaohongshu, Quora, TikTok Shop, Weibo, Zhihu, Substack, and Nextdoor.

Its catalogue contains more than 300 endpoints. Depending on the endpoint, an agent can retrieve profiles, public email data, posts, reels, comments, followers, likers, hashtags, search results, company pages, jobs, advertisements, transcripts, shop products, and local business listings. Endpoint availability and inputs vary by platform, so agents can search the catalogue and inspect an endpoint before making a paid request.

How it works

The InsightSocial MCP server offers five MCP tools: search_endpoints, describe_endpoint, call_endpoint, read_result, and get_credits. Search and description operations are free. call_endpoint makes the API request, stores the complete response, and returns a result identifier with a trimmed view and a command for fetching another page. Each additional page is a separate call.

Saved responses can be reshaped locally with jq expressions, selected fields, item limits, or a structural outline. These operations do not make another network request or incur another charge. The API requests schema 2 for every call, giving supported platforms a shared field layout while recording fields that could not be populated in an unavailable list. A dry-run parameter can return a price quote without charging the account.

Setup and configuration

Run npx -y insightsocial login to authenticate through a browser, or provide an existing key with --api-key. The key is saved locally and the MCP process reads it without placing the secret in the MCP configuration. INSIGHTSOCIAL_API_KEY can also be supplied in the server environment.

Start the local server with npx -y insightsocial mcp. The standard MCP configuration uses npx, the -y option, and the insightsocial mcp arguments. npx -y insightsocial init --yes can write setup entries for Claude Code, Codex, and Cursor. The hosted endpoint is available at https://api.insightsocial.app/mcp; clients that support its authentication flow can use OAuth, while other clients can send a bearer key.

INSIGHTSOCIAL_BASE_URL changes the API base URL from its default. INSIGHTSOCIAL_HOME changes the default local directory for configuration, catalogue cache, and MCP results. Without a key, endpoint search and description remain available, but data calls require authentication.

Tools and capabilities

  • search_endpoints: locate endpoints by keywords and platform.
  • describe_endpoint: show inputs, accepted values, an example, and the endpoint price.
  • call_endpoint: fetch and save complete API responses while returning a reduced view.
  • read_result: inspect saved data with jq, field selection, item limits, or size summaries.
  • get_credits: check account balance, plan, and usage.

The command-line interface also supports listing endpoints, running paths directly, viewing the latest saved result, checking credits, paging through responses, and supplying idempotency or freshness options.

Limitations and notes

Requests are priced per endpoint call. Empty results, failed calls, and idempotent replays are free, but each requested page is charged separately. The shared schema does not guarantee that every platform supplies every field; unavailable values are marked as unknown rather than treated as zero. The service provides public data, and the available information depends on each endpoint and platform.

The local server uses stdio. Results are saved in full locally even when the returned MCP view is trimmed, so agents can reduce context size without discarding the original response.

Read the full README β†’View source on GitHub β†’

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Reviews

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Frequently Asked Questions about InsightSocial

InsightSocial is an MCP server that connects AI agents to the InsightSocial API for live public data from 25 social platforms. Its main tools search and describe endpoints, call endpoints, read saved results, and check credits. Responses use a shared schema and complete results are stored locally for later reshaping.

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Technical Specs & Signals

Category🌐Social Media
More technical detailsExpand β–Ύ
TransportSTDIO
RuntimeNode.js
LicenseMIT
ClientsClaude Desktop, Cursor, Cline / VS Code, Windsurf, Claude Code, VS Code (GitHub Copilot), Zed, OpenAI Codex CLI, Gemini CLI, JetBrains AI Assistant, Roo Code, Continue, LM Studio
Last updatedOct 13, 2026
Views0
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GitHub stars0
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Last commit6d ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Oct 8, 2026
40Quality signal: Fair Β· 40/100How this signal is calculated β–Ύ
Server availabilityNot measured

Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools16/30
Adoption & activity4/15
Community engagement0/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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Critical 0High 0Medium 0Low 0

Scanned 6h ago via OSV.dev Β· insightsocial (npm)

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