HDW MCP Server
The HDW MCP Server (also known as AnySite MCP Server) enables AI agents to access real-time web data from multiple platforms through a unified Model Context Protocol interface.
LinkedIn Integration - Advanced user search with 10+ filters (keywords, title, company, location, industry, education, seniority, job functions, languages), detailed profile extraction (experience, skills, education, posts, reactions, comments, connections, endorsers), email lookup, Sales Navigator search with 2500+ result capacity, company intelligence (profiles, employee lists, posts), post search and analytics, conversation management, and account actions (messages, connection requests, posts, comments)
Instagram Access - User profiles with follower counts, content extraction (posts and reels), engagement analysis (comments and likes), and hashtag/keyword search
Reddit Functionality - Post search with filters (relevance, sorting, time ranges, subreddit targeting), detailed post information with scores, and nested comment thread extraction
Web Scraping & Search - Google search with structured results, general webpage parsing with CSS selectors, and LinkedIn company discovery
Key Features - Bulk operations (1000-2500 results per request), flexible timeout control (20-1500 seconds), URN-based operations for precise targeting, multi-filter support, real-time non-cached data, automatic rate limit management, proxy rotation, error recovery (self-healing APIs), and secure OAuth authentication
Utilizes .env files for configuring API credentials and environment variables required for the server to function.
Supports installation via git clone from the repository for setting up the HDW MCP Server environment.
Enables searching for LinkedIn companies via Google, where the first result is typically identified as the best match.
Offers specific setup instructions and configuration file paths for macOS users to integrate with the HDW MCP Server.
Uses npm for dependency management during the installation process of the HDW MCP Server.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@HDW MCP Serverfind software engineers at Google with 5+ years experience"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Anysite MCP Server
The entire web is your database. Your AI assistant is the query interface.
A Model Context Protocol server that lets Claude, Cursor, ChatGPT, and any MCP client query structured data from LinkedIn, Instagram, Twitter/X, Reddit, YouTube, SEC EDGAR, Y Combinator, Crunchbase, and any URL on the web — through five universal tools.
Quick start
Two ways to connect. Remote MCP is the recommended path for everyday use — managed cache, OAuth, no infrastructure. Self-hosted is for development or when you want the server running locally over stdio.
Option 1: Remote MCP with OAuth (recommended)
Hosted at https://mcp.anysite.io/mcp. Works with Claude Desktop, Claude Code, Cursor, Cline, Windsurf, ChatGPT, and any MCP-compliant client.
Step 1: Sign up
Create an account at anysite.io. The MCP30 promo covers your first month of MCP Unlimited ($30/month, 6 req/min fair-use, no credit counting). Credit-based plans (Starter $49 / Growth $200 / Scale $300 / Pro $549 / Enterprise from $1,199) also include MCP access; see docs.anysite.io/mcp-server/overview.
Step 2: Connect your client
Settings → Connectors → Add Custom Connector
URL:
https://mcp.anysite.io/mcpClick Connect, authorize in the browser
Required: Settings → Capabilities → Tool access → Tools already loaded
The last step is critical. Claude Desktop's "Load tools when needed" mode uses name-based matching that fails on generic names like discover and execute. If you skip it, the tools exist but the model will not reliably call them.
claude mcp add --transport http anysite "https://mcp.anysite.io/mcp?api_key=YOUR_KEY"
claude mcp list # should show: anysite connectedThe URL carries your API key — treat it as a secret.
Edit ~/.cursor/mcp.json (global) or .cursor/mcp.json in the project root:
{
"mcpServers": {
"anysite": {
"url": "https://mcp.anysite.io/mcp?api_key=YOUR_KEY",
"transport": "http"
}
}
}Anysite implements MCP 1.0 over Streamable HTTP with OAuth 2.0. Point any compliant client at https://mcp.anysite.io/mcp and authenticate via OAuth or ?api_key=YOUR_KEY.
Step 3: Verify
Ask the assistant:
What MCP tools do you have from anysite?It should list exactly: discover, execute, get_page, query_cache, export_data.
Step 4: Run a query
Use anysite to find 20 CTOs at Series B fintech startups in New York,
then show me the ones with AI or ML in their headline.The assistant runs discover on LinkedIn, picks the right search endpoint, calls execute, then narrows server-side with query_cache.
Option 2: Self-hosted (npm, stdio)
For local development, custom integrations, or when you want the server in-process. Distributed as @anysiteio/mcp on npm. Runs over stdio; cache lives in-process for 7 days.
Install
npm install -g @anysiteio/mcpOr run on demand with npx -y @anysiteio/mcp.
Configure your client
{
"mcpServers": {
"anysite": {
"command": "npx",
"args": ["-y", "@anysiteio/mcp"],
"env": {
"ANYSITE_ACCESS_TOKEN": "your_token_here"
}
}
}
}That is the entire configuration. Only ANYSITE_ACCESS_TOKEN is required — create one at app.anysite.io.
Related MCP server: Proxycurl MCP Server
What's new in 2.0
The server no longer ships 60+ individual tools. Instead, it exposes five universal meta-tools and discovers the underlying endpoints dynamically from the AnySite OpenAPI spec. This means:
Every new endpoint added to the AnySite API is available the next time the server starts — no package update required.
The agent learns the surface through
discover(source, category)rather than from a static tool catalog.Pagination, filtering and exports are handled in-process via the cache: one
execute()call, then unlimitedget_page/query_cache/export_datacalls without re-paying API credits.
The five tools
Tool | Purpose |
| List endpoints in a category with their params and LLM hints. Always call before |
| Fetch data. Returns first 10 items + |
| Paginate cached items without re-fetching. |
| Filter / sort / aggregate cached items locally. |
| Dump the full dataset to |
Sources surfaced through discover: LinkedIn, Instagram, Twitter/X, Reddit, YouTube, SEC EDGAR, Y Combinator, Crunchbase, DuckDuckGo, the universal web parser, plus AI parsers for GitHub, Amazon, Google Maps, G2, BuiltWith, Apify, GLEIF, Newegg and more. New endpoints appear automatically as soon as they ship on the platform — no package update required.
Usage pattern
discover("linkedin", "search")
→ endpoints: ["users", "companies", "posts", ...] with params
execute("linkedin", "search", "users", { keywords: "CTO AI" })
→ { items: [...first 10], total: 50, cache_key: "abc..." , next_offset: 10 }
get_page("abc...", offset=10) # next page, free
query_cache("abc...", { conditions: [{ field: "location", op: "contains", value: "San Francisco" }] })
export_data("abc...", "csv") # dump everything to a CSV fileExample: find decision makers and export to CSV
1. discover("linkedin", "search")
2. execute("linkedin", "search", "users", { keywords: "CTO", company_keywords: "AI" })
3. query_cache(cache_key, { conditions: [{ field: "location", op: "contains", value: "Berlin" }] })
4. export_data(cache_key, "csv")The agent figures out the parameter names on its own from discover.
Skills — ready-made workflows
The MCP server gives raw access. Anysite Skills package that access into named workflows you summon by topic, so the assistant runs a proven pattern instead of improvising. Built for Claude Code (also works in Cursor / Windsurf via the same plugin format).
Workflow | What you say | What it does |
Lead generation | "Find me 50 marketing directors at Series A SaaS in Berlin and enrich with email" | LinkedIn search → enrichment → CSV |
Competitor intelligence | "Track @competitor across LinkedIn hires, social, YC, and recent posts" | Multi-source intel + hiring velocity + sentiment |
Person analyzer | "Deep-dive on this LinkedIn profile before our partnership call" | LinkedIn + Twitter + Reddit + GitHub + web → strategic brief |
Market research | "Map the AI legal-tech landscape — startups, funding, momentum" | YC + Crunchbase + SEC + Reddit + Twitter sentiment |
Customer pain mining | "Pull verbatim complaints about Salesforce from Reddit and Twitter" | Pain clusters + exact quotes + white-space gaps |
Brand reputation | "What is the conversation around our brand this week?" | Cross-platform mention scan with sentiment scoring |
Positioning map | "Plot 3-5 competitors on a positioning map, find the empty quadrant" | Five-axis comparison + positioning statement |
Full catalog (17 skills, including VC analyst, influencer discovery, audience analysis, content analytics, trend analysis): github.com/anysiteio/agent-skills.
Install
In Claude Code:
/plugin marketplace add https://github.com/anysiteio/agent-skills
/plugin install anysite-lead-generation@anysite-skillsYou can install one skill or the whole marketplace. The MCP server connection above is the only prerequisite.
Local development
git clone https://github.com/anysiteio/anysite-mcp.git
cd anysite-mcp
npm install
npm run build:tsc
ANYSITE_ACCESS_TOKEN=... node build/server.jsInspect the tools interactively:
npm run inspectorConfiguration
Env var | Required | Default | Notes |
| yes | — | Create one at app.anysite.io |
| no |
| Override the API base |
| no |
| Override the spec URL |
Project layout
src/
├── server.ts stdio entry (CLI bin)
├── index.ts Smithery TypeScript runtime adapter
├── loader.ts fetches and parses the OpenAPI spec
├── registry.ts in-memory source/category/endpoint registry
├── client.ts HTTP client with retry/timeout
├── cache.ts cache_key → items
├── query.ts in-memory filter / sort / aggregate
├── export.ts json / jsonl / csv writers
├── tools.ts the five meta-tool handlers
├── tool-schemas.ts MCP tool input schemas (zod + JSON Schema)
├── instructions.ts instructions text for the LLM
├── config.ts env-derived constants
└── types.ts shared typesLicense
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