"Semantic Search API Solutions" matching MCP servers:

MCP server for B2B lead generation and company search using the Generect Live API. Provides tools to search leads, companies, generate emails, and get lead by URL.

Enables LLMs to search and retrieve Autotask tickets, companies, and contacts using advanced semantic search and AI-powered reranking.

A read-only MCP server for Portal.io that enables browsing proposals, users, contacts, and catalog items through secure HMAC-signed API requests.

Connects AI agents to Yuki accounting via SOAP API, enabling management of administrations, relations, invoices, transactions, and documents through natural language.

MCP server enabling AI assistants to connect to Kula recruiting API for managing jobs, candidates, applications, webhooks, and more.

Enables MCP clients to search and execute 360 operations across Holded's accounting, sales, inventory, contacts, CRM, projects, team, calendar, inbox, and developer APIs. Supports read and write calls with an API key, including a read-only mode.

Exposes native OnlyFans and Fansly access as MCP tools, letting agents read fans, messages, media, earnings, posts, transactions and subscribers across connected creators, with opt-in outbound writes. It also provides CRM tags, smart links, webhooks and bulk exports through a single API key.

Enables AI agents to search companies, enrich contacts, and reveal emails via Fiber AI's data and tools directly from the editor.

Connects Claude Desktop or Claude Code to a company's Odoo instance with a one-click extension or installer, automatically negotiating the right API (web session, JSON-2, or JSON-RPC) for any Odoo version. Exposes tools that let Claude search, read, count, group, create, update, delete, and link Odoo records as the logged-in user, with an optional read-only mode.

A comprehensive Model Context Protocol (MCP) server that provides complete access to the Recharge Storefront API endpoints. Enables AI assistants to manage subscriptions, customers, orders, and billing through a standardized interface.

A production-style MCP server exposing six business tools (web search, database, CRM, email, calendar, analytics) to AI clients via a secure, authenticated interface, with mock mode and a reference agent client.

Enables AI assistants to interact with HubSpot CRM data, providing tools for managing contacts and companies, retrieving activity and conversations, and performing semantic search with vector storage and caching for improved performance.

Enables AI assistants to access and manage HeadHunter job platform data, including vacancies, resumes, negotiations, and employer settings via 167+ tools.

Enables AI agents to manage GoHighLevel sub-account CRM data, including contacts, custom fields, tags, workflows, and calendar configurations through natural language.

Find professional email addresses from name + company domain. Tests 15+ patterns against MX records with confidence scoring, with pay-per-call via x402.

Enables AI assistants to query and maintain Microsoft Dataverse and Dynamics 365 Customer Engagement environments via MCP, with 84 tools for records, metadata, web resources, plugin registration, data model management, diagnostics/audit, solutions, and classic Ribbon customization.

Verified, long-tail company search: describe what you want, get an LLM-verified company shortlist.

Enables semantic search of Salesforce case summaries using embeddings, accessible via MCP tools and REST API.

Enables searching for volunteer opportunities via MCP protocol, REST API, and includes a custom Apex MCP client for Salesforce Agentforce integration, all powered by the free VolunteerConnector API.

Enables AI assistants to directly access and manage HubSpot CRM data, including contacts, companies, and conversations, with semantic search and caching for improved performance.

Enables AI assistants to interact with HubSpot CRM data by creating contacts and companies, retrieving activity and recent conversations, and performing semantic search across previously retrieved records with built-in caching and vector storage.

Enables AI assistants to access and manage HubSpot CRM data, including contacts, companies, activity, conversations, and semantic search over cached interactions while improving response times via built-in vector storage and caching.

Enables AI agents to extract structured firmographic data from public LinkedIn company URLs, returning fields like name, industry, size, and headquarters.

Enables AI assistants to interact with HubSpot CRM data, including contacts, companies, and engagement information, with semantic search over previously retrieved data and built-in caching/vector storage to improve response times.

Enables AI assistants to interact with HubSpot CRM data by creating and retrieving contacts, companies, and recent activity, while providing semantic search over stored conversations with vector storage and caching.

Enables AI assistants to interact with HubSpot CRM data, including creating contacts and companies, retrieving recent activities and conversations, and performing semantic search over previously retrieved data. It uses built-in vector storage and caching to work around API limitations and improve response times.

Enables AI assistants to interact with HubSpot CRM data through tools for contacts, companies, activity, conversations, and semantic search, with vector storage and caching to improve response times.

Enables AI assistants to create and retrieve contacts, companies, activity, and conversation threads directly in a CRM account through natural-language prompts. Includes built-in vector storage and caching for semantic search over previously retrieved data, improving response times despite API limitations.

MCP server that provides mock APIs and deterministic seed data for ERP/OMS, WMS, and CRM systems, enabling supply chain data exploration and integration testing.

Enables AI assistants to interact with HubSpot CRM data by creating and retrieving contacts, companies, activity, and conversations, while supporting semantic search over previously retrieved data. Built-in vector storage and caching help improve performance and work around API limitations.

Enables AI assistants to interact with HubSpot CRM data, including contacts, companies, engagement, conversations, and semantic search over previously retrieved data, with vector storage and caching to overcome API limitations and improve response times.

Enables AI assistants to interact with HubSpot CRM data for contacts, companies, activity, conversations, and semantic search, with built-in vector storage and caching to overcome API limitations and improve response times.

Enables AI assistants to interact with HubSpot CRM data, including contacts, companies, and engagement data. It provides built-in vector storage and caching to support semantic search and faster responses.

Provides tools to interact with Odoo 19's External JSON-2 API, enabling CRUD operations and complex queries on Odoo databases with multi-company support.

Enables AI assistants to interact directly with HubSpot CRM data, including contacts, companies, activities, conversations, and semantic search over previously retrieved data. Built-in vector storage and caching help overcome API limitations and improve response times.

Enables AI assistants to interact with HubSpot CRM data, including contacts, companies, and engagement activities, with built-in vector storage and caching for semantic search and improved response times.

Enables AI assistants to interact with HubSpot CRM data, including creating and searching contacts and companies, retrieving activity and conversations, and using vector storage for semantic search across prior interactions.

This MCP server simplifies interaction with the ConnectWise Manage API through API discovery, execution, and a fast memory system for efficient workflows.

Enables AI assistants to interact with HubSpot CRM data, creating contacts and companies with duplicate prevention, retrieving company activity, active contacts and companies, and recent conversation threads. Built-in FAISS vector storage, thread-level indexing, and embedding caching provide semantic search over previously retrieved data to overcome HubSpot API limits and improve response times.

Enables AI assistants to interact with HubSpot CRM data by accessing contacts, companies, activity, and conversations, while providing vector-backed semantic search and caching for faster, more reliable workflows.