| 1 |
| Ecosystem | 1 | 1 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 7 decomposed | 11 decomposed |
| Times Matched | 0 | 0 |
Exposes geographic data APIs through the Model Context Protocol, enabling Claude and other MCP-compatible assistants to query location information, coordinates, and place names via standardized tool schemas. Implements MCP resource and tool handlers that translate natural language requests into structured geographic queries, returning GeoJSON-compatible location objects with latitude, longitude, and administrative boundaries.
Unique: Implements geographic lookup as a first-class MCP tool with bidirectional geocoding (address→coordinates and coordinates→address) rather than wrapping a generic HTTP client, enabling Claude to reason about location context natively within conversation flow
vs alternatives: Tighter integration with MCP protocol than generic API wrapper tools, allowing Claude to invoke geographic queries with natural language without explicit JSON formatting or API key management by the user
Provides real-time currency exchange rates through MCP tool handlers that accept source and target currency codes, returning current bid/ask spreads and conversion rates. Implements caching at the MCP server level to reduce redundant API calls within a conversation session, with configurable TTL for rate freshness. Supports multi-currency queries and historical rate context when available from the upstream Apogeio API.
Unique: Implements server-side rate caching with configurable TTL within the MCP server process, reducing API calls for repeated currency queries in the same conversation without requiring Claude to manage cache state
vs alternatives: More efficient than calling a generic HTTP tool for each rate lookup because the MCP server maintains session-level cache, reducing latency and API quota consumption compared to stateless tool wrappers
Exposes IP geolocation capabilities through MCP tools that accept IPv4 or IPv6 addresses and return geographic location (country, city, coordinates), autonomous system number (ASN), ISP name, and connection type. Uses the Apogeio IP geolocation API backend with structured response parsing, enabling Claude to understand network origin and infrastructure context. Supports batch IP lookups within a single tool invocation for efficiency.
Unique: Combines three data dimensions (geographic location, ASN, ISP) in a single MCP tool response rather than requiring separate API calls, enabling Claude to correlate network infrastructure with location in a single reasoning step
vs alternatives: More comprehensive than standalone IP lookup tools because it includes ASN and ISP resolution alongside geolocation, providing network context that generic geolocation APIs omit
Implements a fully-compliant MCP server that registers geographic, exchange rate, and IP geolocation tools using the MCP tool schema specification. Handles MCP protocol handshake, resource discovery, and tool invocation lifecycle. Built with proper error handling, request validation, and response serialization to ensure compatibility with Claude Desktop, Cursor, and other MCP hosts. Supports both stdio and HTTP transport modes for flexible deployment.
Unique: Provides a reference implementation of MCP server architecture with proper lifecycle management, error handling, and transport abstraction, rather than a minimal proof-of-concept
vs alternatives: More production-ready than example MCP servers because it includes proper validation, error recovery, and support for both stdio and HTTP transports, reducing integration friction for Claude Desktop and Cursor users
Registers the apogeoapi-mcp server with the Smithery MCP package registry, enabling one-click installation in Claude Desktop and Cursor via the registry UI. Implements standardized package metadata (name, version, description, dependencies) and configuration schema that Smithery uses for automated server discovery and installation. Supports automatic updates through Smithery's version management system.
Unique: Leverages Smithery's standardized package format and auto-discovery mechanism, enabling one-click installation without manual configuration files or environment variable setup
vs alternatives: Simpler distribution than manual MCP server setup because Smithery handles dependency resolution, version management, and configuration schema validation automatically
Implements MCP protocol compliance that works across Claude Desktop, Cursor, and other MCP-compatible AI assistants through abstraction of client-specific transport and capability negotiation. Detects client capabilities during handshake and adapts tool schemas and response formats accordingly. Handles version negotiation and graceful degradation for older MCP protocol versions.
Unique: Implements client capability detection and graceful degradation rather than assuming a single client implementation, enabling the same server binary to work across Claude Desktop, Cursor, and future MCP hosts
vs alternatives: More portable than client-specific MCP servers because it negotiates capabilities at runtime rather than hardcoding assumptions about client features
Implements comprehensive input validation and error handling for all MCP tool invocations, including type checking, parameter bounds validation, and API error translation. Returns structured error responses with actionable error messages and retry guidance. Validates IP addresses, currency codes, and geographic coordinates before forwarding to upstream APIs, reducing unnecessary API calls and providing immediate feedback to Claude.
Unique: Performs pre-flight validation before calling upstream APIs (e.g., IP address format check, currency code validation) rather than relying solely on API error responses, reducing latency and API quota waste
vs alternatives: More efficient than naive API forwarding because it catches invalid inputs locally before making network calls, improving user experience and reducing API costs
Executes web searches via the Tavily API and returns structured results with relevance scoring, source attribution, and clean text extraction optimized for LLM consumption. The MCP server marshals search queries through an axios HTTP client configured with the Tavily API key, parses JSON responses containing ranked results with URLs and snippets, and formats output for direct consumption by language models without additional preprocessing.
Unique: Tavily's search results are specifically optimized for LLM consumption with relevance scoring and clean formatting, rather than generic web search results. The MCP server wraps this via StdioServerTransport, enabling seamless integration into Claude Desktop and other MCP clients without custom HTTP handling.
vs alternatives: Returns LLM-ready formatted results with relevance scores out-of-the-box, whereas generic search APIs (Google, Bing) require additional parsing and ranking logic to be LLM-friendly.
Extracts clean, structured content from specified URLs using the Tavily extract endpoint, handling HTML parsing, boilerplate removal, and content normalization automatically. The server sends URLs to Tavily's extraction service via axios, receives parsed markdown or structured text, and returns content ready for LLM ingestion without requiring the client to manage web scraping libraries or HTML parsing.
Unique: Tavily's extraction service is optimized for LLM-ready output (markdown formatting, boilerplate removal, semantic structure preservation) rather than generic web scraping. The MCP server exposes this as a tool that agents can call directly without managing external scraping libraries.
vs alternatives: Handles boilerplate removal and content normalization automatically, whereas Puppeteer or Cheerio require custom logic to identify main content and remove navigation/ads.
Tavily MCP Server scores higher at 62/100 vs apogeoapi-mcp at 46/100. apogeoapi-mcp leads on adoption, while Tavily MCP Server is stronger on quality and ecosystem.
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Provides pre-built configuration templates and integration guides for popular MCP clients (Claude Desktop, Cursor, VS Code, Cline), including JSON configuration snippets for claude_desktop_config.json, cursor settings, VS Code extensions, and Cline agent configuration. Each integration template specifies the MCP server command, environment variables, and client-specific setup steps.
Unique: Official Tavily MCP provides pre-built integration templates for major MCP clients (Claude Desktop, Cursor, VS Code, Cline), reducing setup friction. Each template includes specific configuration syntax and environment variable requirements for that client.
vs alternatives: Pre-built templates eliminate guesswork in client configuration, whereas generic MCP documentation requires users to adapt examples for Tavily-specific setup.
Crawls websites starting from a seed URL and recursively follows internal links up to a specified depth, extracting content from each page and returning a structured collection of crawled pages. The server manages crawl state through Tavily's crawl endpoint, controlling recursion depth and link-following behavior, and returns all discovered pages with their extracted content and metadata for bulk analysis or knowledge base construction.
Unique: Tavily's crawl service is designed for LLM-friendly bulk extraction with automatic content normalization across multiple pages, rather than generic web crawlers that return raw HTML. The MCP server exposes depth control and link-following as tool parameters, enabling agents to autonomously decide crawl scope.
vs alternatives: Handles content extraction and normalization across all crawled pages automatically, whereas Scrapy or Selenium require custom pipelines to extract and normalize content from each page individually.
Analyzes a website's structure and generates a semantic map of URLs organized by topic or content type, enabling agents to understand site organization without manual exploration. The tavily_map tool sends a seed URL to Tavily's mapping service, which crawls the site, clusters pages by semantic similarity, and returns a hierarchical structure of discovered URLs grouped by inferred topic or purpose.
Unique: Tavily's map tool uses semantic clustering to organize URLs by inferred topic rather than just crawling and returning a flat list. This enables agents to navigate large sites intelligently without exhaustive crawling.
vs alternatives: Provides semantic site structure discovery out-of-the-box, whereas generic crawlers return unorganized URL lists requiring post-processing to identify topic-relevant pages.
Orchestrates multi-step research workflows where an agent autonomously decides which search, extraction, and crawling steps to perform based on intermediate results. The tavily_research tool wraps the other four tools and manages state across multiple API calls, allowing agents to refine queries, follow promising leads, and synthesize findings without explicit step-by-step instruction from the user.
Unique: The research tool enables agents to autonomously orchestrate search, extraction, and crawling steps based on intermediate findings, rather than requiring explicit tool calls for each step. This leverages the agent's reasoning to decide research strategy dynamically.
vs alternatives: Enables autonomous research workflows where agents decide next steps based on findings, whereas manual tool-calling requires explicit user or system prompts to specify each search or extraction step.
Implements the Model Context Protocol (MCP) server specification using TypeScript and StdioServerTransport, enabling the Tavily tools to be exposed as MCP tools callable by any MCP-compatible client. The server registers tool handlers via setRequestHandler(ListToolsRequestSchema, ...) and CallToolRequestSchema, marshaling tool calls from clients through to Tavily API endpoints and returning results in MCP-compliant format.
Unique: Official Tavily MCP server implementation using StdioServerTransport for direct process communication, enabling zero-configuration integration into Claude Desktop and other MCP clients. Supports both remote (hosted) and local deployment models.
vs alternatives: Official MCP implementation ensures compatibility and feature parity with Tavily API, whereas third-party MCP wrappers may lag behind API updates or lack full feature support.
Supports both remote deployment (hosted at https://mcp.tavily.com/mcp/) and local self-hosted deployment (via NPX, Docker, or Git), with different authentication models for each. Remote deployment uses URL parameters or Bearer token headers for API key passing, while local deployment uses TAVILY_API_KEY environment variable. Both expose identical tool capabilities through the same MCP interface.
Unique: Official Tavily MCP provides both remote (zero-setup) and local (self-hosted) deployment options with identical tool capabilities, enabling users to choose based on security, latency, and infrastructure requirements. Remote uses OAuth and Bearer tokens; local uses environment variables.
vs alternatives: Dual deployment model provides flexibility that single-deployment solutions lack; users can start with remote for quick testing and migrate to local for production without code changes.
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