"Qdrant vector database and search engine" matching MCP servers:

An MCP-native CRM backend for AI agents, enabling customer, opportunity, note, follow-up, and pipeline health management through 15 MCP tools.

An archived MCP server providing 14 tools (bant_qualify, ocr_extract, asr_transcribe, etc.) originally built on Python/FastAPI/Cloud Run.

Enables an AI client to track a watch list of contacts and retrieve only what changed since the last run — departures, new employers, replacements, and new hires after a role closed — each row carrying match evidence, source dates, and ready-to-use outreach payloads. It runs the analysis on Apify using the caller's own provider keys, supports stored or caller-held state, and can push results to a signed webhook.

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

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

Provides interactive tools to explore AFAS customer data and employee leave information, including bubble charts, leave balance reports, and detailed leave cards.

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.

MCP server that connects to a sales CRM database, enabling AI agents to search prospects, view pipeline status, manage follow-ups, and update records using natural language commands.

Enables AI assistants to search and retrieve B2B leads and company data from the LeadBrew database, including contact details and company information.

Deal Strategy & Sales Enablement Engine - 12 tools for sales execution, deal management, and revenue acceleration.

MCP server for Apollo.io B2B database enabling people and company search, enrichment, and insights through conversational interfaces.

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.

Resume parsing & candidate matching engine (European markets - ONSS/DIMONA compliance).

Connects a podcast-sponsorship database to AI assistants, allowing users to search for brands that sponsor podcasts and reveal buyer contacts by name and email.

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.

Turns a recruitment database into an AI-queryable pipeline, enabling natural language queries to search contractors, build shortlists, draft outreach, and book engagements.

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 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, including creating contacts and companies, retrieving activity and conversations, and performing semantic search over stored interactions while using vector storage and caching for faster responses.

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