"Information about Unreal Engine" matching MCP servers:

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.

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

Provides tools for AI assistants to interact with a WooCommerce store, enabling fetching recent orders with optional filtering and retrieving detailed information about specific orders by ID.

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

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 Claude Desktop to query ServiceTitan data about technician jobs and business performance via natural language, while protecting customer personal information.

Enables natural-language queries about sales metrics, returning interactive charts inline in chat via MCP Apps with a markdown fallback for unsupported hosts.

AI-powered lead qualification engine. Ingest leads from any source, auto-enrich with company data, score 0-100 using weighted AI rules, and export to HubSpot, Pipedrive, Google Sheets, CSV, or JSON. 8 MCP tools + 3 resources.

LinkedIn prospect intelligence inside Claude. It automates the research behind outreach, not the sending: scrapes posts, profiles and comment threads into a local SQLite database, classifies what a person or company actually posts about, mines comment threads for people already describing your problem, and surfaces uncommon commonalities worth opening with.

Read-only MCP server for Gingr pet-care facility data, enabling queries about owners, animals, reservations, appointments, services, and staff via natural language.

Model Context Protocol server for the Apideck Unified API. Connect any MCP-compatible agent framework to 100+ accounting systems, HRIS platforms, file storage providers, and more through one integration. More information https://www.apideck.com/mcp-server

Connects AI agents to the Ploomes CRM REST API, exposing 56 tools for managing contacts, deals, tasks, pipelines, interactions, quotes, orders, products, fields, users, and account information.

Manage Job using MCP: Manage Job, Candidates, Resumes, Salaries all within this one MCP tools It can solve problems like: You have 50 resumes to screen. Your AI assistant can reason about candidates, but it can't: Read PDFs/DOCX — The AI can't open binary files Extract structured data — Copy-pasting loses formatting, metrics, and context Compare at scale — No consistent scoring across candida

A read-only MCP server for the Little Green Light donor CRM. It lets Claude answer questions about donor data, gifts, and fundraising metrics by querying LGL directly.

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

Provides AI assistants access to YOUREPT CRM admin data, including leads, students, teachers, lessons, payments, payouts, and financial reports, enabling natural-language queries about business metrics.

The Derrick MCP server provides AI assistants with access to Derrick's B2B enrichment capabilities. It allows retrieval of company and contact information, lead enrichment, prospecting automation, and workflow execution directly through the Model Context Protocol (MCP).

Provides tools to search for people using registered business cards and the public Eight network. Enables LLMs to query person information while keeping private data secure.

Enables Claude to answer plain-English questions about a GTM engineer agent's own work — client ICPs, run history and costs, buying-signal alerts, lists, and ranked prospect fit scores — by reading the research files that agent writes, with every answer citing its source file. It also exposes one guarded action tool that starts a new prospect research run only after a cost preview, an explicit confirmation, and daily run/spend cap checks.