Social Intel MCP
The Social Intel MCP server enables AI agents to discover Instagram influencers for brand outreach, research, and creator intelligence workflows — with pay-per-call pricing in USDC via the x402 protocol, no API keys or subscriptions required.
Core capability: Use the search_leads tool to find Instagram influencers with filters including:
Keyword — search by name or bio content (e.g.,
yoga,travel blogger,NYC chef)Location — filter by country (ISO code or full name) and/or city
Category — target niches like Fitness, Beauty, Travel, Food & Beverage, Gaming, Fashion, Lifestyle, and Sports
Gender — restrict to
maleorfemalecreatorsFollower range — set min/max follower counts to target micro-influencers (10K+), macro-influencers (100K+), etc.
Result size — request 1–100 results per call
Profile data returned: Username, full name, follower count, category, bio, public email (~50% of accounts), verified status, and business account status.
Free demo mode: Set demo=true to get up to 3 preview results with no payment, ideal for validating filters before a paid search.
Pricing (USDC via x402 on Base or Solana): $0.50 for 1–20 results, $0.80 for 50, $1.30 for 100. Payments are handled automatically via compatible x402 client libraries.
Integration: Supports stdio, HTTPS, and SSE transports, compatible with Claude Desktop, Cursor, VS Code, Cline, and other MCP clients.
Search and retrieve Instagram influencer profiles with filters like keyword, location, category, gender, and follower count, returning public email and profile metadata.
Social Intel MCP
Instagram influencer discovery for AI agents. Pay per call in USDC via x402 — no API keys, no subscriptions, no sign-up.
socialintel.dev is a data layer for AI agents running influencer-outreach, brand-research, and creator-intelligence workflows. This repository ships an MCP server that exposes the same data through the Model Context Protocol so any MCP-compatible client (Claude, Cursor, VS Code, Cline, …) can call it natively.
📋 Table of Contents
Related MCP server: pulsenetwork-mcp
🚀 Quickstart — hosted endpoint
Recommended. Point any MCP client that speaks HTTP/SSE or streamable transport directly at our hosted server:
https://socialintel.dev/mcpNo install, no pip, no Docker. Your agent's x402 client handles payment on
each tools/call.
If your client needs a stdio wrapper (Claude Desktop on older versions, some
CLI clients), see the MCP clients section for uvx /
pip install setups that proxy stdio → HTTPS.
🔌 MCP clients
Claude Desktop
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"socialintel": {
"command": "uvx",
"args": [
"--from",
"git+https://github.com/socialintel/socialintel-mcp",
"socialintel-mcp"
],
"env": {
"SOCIAL_INTEL_API_URL": "https://socialintel.dev"
}
}
}
}Restart Claude Desktop. search_leads appears in the tool list.
Cursor
Preferences → MCP → add server:
{
"socialintel": {
"command": "uvx",
"args": ["--from", "git+https://github.com/socialintel/socialintel-mcp", "socialintel-mcp"]
}
}VS Code (with GitHub Copilot or Continue)
.vscode/mcp.json in your workspace:
{
"servers": {
"socialintel": {
"command": "uvx",
"args": ["--from", "git+https://github.com/socialintel/socialintel-mcp", "socialintel-mcp"]
}
}
}Cline (VS Code extension)
Cline auto-detects MCP servers from cline_mcp_settings.json. Add the same
server block as Claude Desktop above.
Cherry Studio / Zed / any MCP-compatible client
Use the stdio command:
uvx --from git+https://github.com/socialintel/socialintel-mcp socialintel-mcpOr point the client at the hosted HTTP endpoint if it supports remote MCPs:
https://socialintel.dev/mcp
Direct pip install
pip install git+https://github.com/socialintel/socialintel-mcp
SOCIAL_INTEL_API_URL=https://socialintel.dev socialintel-mcp🛠️ Tools
search_leads
Search Instagram influencers by demographics, location, keyword, or business category.
Param | Type | What it does |
| string | Keyword on name/bio (e.g. |
| string | ISO code ( |
| string | City filter (e.g. |
| string |
|
| string |
|
| int | Floor. |
| int | Ceiling. |
| int | 1–100 (default 20). Price scales with limit |
| bool |
|
Each result:
{
"username": "yoga_with_adriene",
"full_name": "Adriene Mishler",
"followers": 10500000,
"category": "Fitness",
"bio": "Yoga teacher & filmmaker from Austin TX",
"public_email": "contact@adriene.com",
"is_verified": true,
"is_business": true,
"gender": "woman"
}public_email is populated where available — higher on business-verified
accounts, lower on personal creator accounts (Instagram platform reality,
not a filter we apply).
💰 Payment flow (x402)
Agent payments follow the x402 protocol: a 402 Payment Required response carries signed payment requirements; the client signs a USDC transfer and retries; the server verifies + settles through a facilitator and returns results.
Agent calls
search_leads(category="Fitness", country="US").Server replies
HTTP 402withextensions.bazaarmetadata and accepts blocks for Base (USDC) and Solana (USDC).If the client runs an x402 client library (
x402-httpx,agentcash, the TypeScriptx402package, etc.), it signs a transfer on either chain and retries.Our server verifies + settles via the CDP facilitator (primary — also catalogues us on agentic.market) or PayAI facilitator (fallback). Results return on the retried call.
Pricing — transparent per-call, no minimums:
Limit | USDC |
1–20 | $0.50 |
50 | $0.80 |
100 | $1.30 |
Formula: $0.50 + max(0, limit − 20) × $0.01.
Free demo with demo=true skips payment entirely; see
Free demo mode.
🎯 Use cases
Micro-influencer discovery for brand outreach
search_leads(
category="Beauty",
country="US",
min_followers=15000,
max_followers=200000,
limit=50,
)Returns 50 beauty micro-influencers in the US, with public business emails where available.
Local creator sourcing (city-level)
search_leads(
city="Los Angeles",
category="Food & Beverage",
min_followers=10000,
limit=20,
)LA food creators with 10K+ followers.
Keyword + demographics fusion
search_leads(
query="personal trainer",
gender="female",
country="United Kingdom",
min_followers=50000,
max_followers=500000,
)Female personal trainers in the UK, mid-to-large follower tier.
Free exploration before paying
search_leads(category="Travel", country="Germany", demo=True)Returns 3 preview results with no payment — perfect for validating filters before spending.
🎛️ Configuration
Env var | Default | Purpose |
|
| Base URL for the upstream API. Set to |
| (empty) | Optional — if set, the MCP server emits anonymous usage events to PostHog. Empty by default so there's no silent telemetry. |
|
| Only used when |
🧪 Free demo mode
Pass demo=true on any search_leads call. You get up to 3 preview
results, no payment required. The response includes an upgrade_message
pointing at the paid URL so your agent can switch to paid mode after
validating filters.
Demo is rate-limited to 5 requests per IP per hour. It reads from our cache rather than the live data source, so content reflects recent queries rather than live platform state.
🌐 Multiple transports
stdio (default) —
uvx --from git+... socialintel-mcpHTTPS / streamable — connect directly to
https://socialintel.dev/mcpSSE — the hosted endpoint also serves Server-Sent Events for clients that prefer it
The hosted endpoint is the simplest path — zero install, identical tool definitions.
🔒 Privacy & telemetry
This server emits one anonymous event per tool call when POSTHOG_API_KEY
is set:
mcp_search_leads— includes only the filter shape (query, country, category, gender, follower range, limit, demo flag) and the resulting row count. No profile usernames, no emails, no payer addresses.
Events are off by default (no key means no capture). If you enable
telemetry you can point it at your own PostHog project — set
POSTHOG_API_KEY to your own key and the events go to your instance, not
ours.
Payment-level telemetry (x402 settle, transaction hashes, revenue) is captured server-side by socialintel.dev, not by this MCP wrapper.
🗺️ Related
Website: socialintel.dev
API docs: socialintel.dev/docs
OpenAPI spec: socialintel.dev/openapi.json
x402 protocol: x402.org
agentcash (x402 CLI/SDK): github.com/merit-systems/agentcash
Base network (USDC): basescan.org
CDP Bazaar discovery: agentic.market
Model Context Protocol: modelcontextprotocol.io
📄 License
MIT — see LICENSE.
🐛 Issues
Bug reports, feature requests, agent-integration questions: github.com/socialintel/socialintel-mcp/issues
Available Tools
1 toolsearch_leadsA
Search Instagram influencers by demographics, location, or keyword.
Returns username, bio, follower count, category, and business email (~50% of accounts).
Price: $0.50 USDC on Base or Solana via x402 (auto-handled by AgentCash or x402 client). Set demo=True to try for free — returns up to 3 results, no payment required.
| Name | Required | Description | Default |
|---|---|---|---|
| query | No | Keyword or phrase to search by name/bio (e.g. 'yoga', 'travel blogger', 'NYC chef'). | |
| country | No | Country filter. ISO code (US, DE, FR, UK, CA, AU, IN, BR, JP) or full name. Default: all countries. | |
| city | No | City filter (e.g. 'Los Angeles', 'London', 'New York'). Use with country for precise local targeting. | |
| category | No | Instagram business category. Examples: Fitness, Beauty, Travel, Food & Beverage, Gaming, Fashion, Lifestyle, Sports. | |
| gender | No | Gender filter: 'male' or 'female' (also accepts 'man'/'woman'). | |
| min_followers | No | Minimum follower count. Use 10000 for micro-influencers, 100000 for macro-influencers. | |
| max_followers | No | Maximum follower count. Use 100000 to exclude celebrities and large brands. | |
| limit | No | Results to return (1-100, default 20). Pricing: 1-20=$0.50, 50=$0.80, 100=$1.30. | |
| demo | No | True = free preview (3 results, no payment). False = full paid search via x402. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description covers pricing ($0.50 USDC on Base or Solana via x402), demo mode limitations (3 results, free), and notes that ~50% of accounts have a business email. This goes beyond what annotations would typically provide.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded with purpose and return fields. Pricing details are valuable but could be slightly more concise. Overall efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 9 parameters with full schema documentation and no output schema, the description covers pricing, demo mode, and email availability. This is sufficient for an agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the description adds limited meaning beyond schema. It only mentions query, country, city, etc., but the schema already documents parameters well. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool searches Instagram influencers by demographics, location, or keyword, and specifies what it returns (username, bio, follower count, category, business email). This clearly defines the action and output, distinguishing it from potential siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use demo mode vs paid mode, but does not provide direct alternatives or when-not-to-use scenarios. Since there are no sibling tools, this is acceptable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
TDQS
Only one tool exists, so there is no risk of confusion between tools.
With only one tool, naming is consistent by default. The verb_noun pattern is followed.
A single tool is insufficient for a server titled 'Social Intel MCP' which implies broader capabilities like lead management or analytics, resulting in a thin offering.
The server only provides search for leads, missing essential operations like saving leads, viewing saved lists, or updating contact information, leaving significant gaps.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
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