"A server for finding information about Bitrix24" matching MCP servers:

Enables AI agents to interact with Bitrix24 CRM through comprehensive tools for managing contacts, deals, leads, companies, tasks, and users, with advanced filtering, search capabilities, and sales team performance monitoring.

Enables AI agents to interact with Bitrix24 CRM for managing contacts, deals, tasks, and leads via a comprehensive set of tools. It supports advanced features like sales team monitoring, performance analytics, and automated CRM searching.

An integration server that enables AI agents to securely interact with Bitrix24 CRM data like contacts and deals via the Model Context Protocol. It provides standardized tools and resources for searching, retrieving, and updating CRM entities through the Bitrix24 REST API.

A comprehensive MCP server for Bitrix24 CRM integration that enables AI agents to manage contacts, deals, tasks, leads, and companies. It also provides advanced tools for sales team monitoring, performance analytics, and automated CRM search capabilities.

An MCP to give AI agents extensive knowledge of your personal finances and control of your budgeting.

Provides read-only access to the Planning Center People API, enabling natural language queries for people, households, background checks, and lists.

Enables AI agents to interact with Salesforce CRM data by executing SOQL queries and managing records. It provides tools for object metadata discovery and record operations, specifically optimized for Heroku deployment.

Enables Claude Desktop to answer natural-language questions about customers by exposing search, profile, order history, status filter, and spend statistics tools backed by local mock data, with a single-file swap path to Oracle AI Agent Studio later.

A Model Context Protocol server for Hatch API integration that provides tools for finding and verifying contact information including emails, phone numbers, LinkedIn profiles, and company data.

Enables AI agents to safely operate HubSpot CRM contacts, deals, and pipelines via MCP, with caching, idempotency, audit trails, and robust error handling.

Resolves a company domain to its LinkedIn company page URL. Lightweight enrichment tool for sales and prospecting workflows.

Unified MCP server combining Hunter.io email finding with Apollo company intelligence for B2B lead enrichment.

Read-only, PII-masked MCP server for querying data federated through DuckDB — list sources/tables, inspect schemas, and run SQL across Postgres, MySQL, SQLite, Snowflake, BigQuery, Excel, and files, governed per source/table/column by a charter.yaml contract. Snowflake, BigQuery, Excel, and files, governed per source/table/column by a charter.yaml contract.

Enables AI agents to perform comprehensive person and company lookups by integrating directly with the Lusha API for business contact enrichment. It provides tools for bulk contact identification via LinkedIn URLs, emails, or names, alongside detailed company information retrieval.

Read-only MCP server for Pipedrive that provides a digest-ready sales queue with overdue follow-ups, due today activities, and deals missing next action.

Enables an AI assistant to answer customer-success questions by synthesizing simulated billing, support ticket, and product usage data into composite churn-risk scores, bands, and plain-language explanations for fictional accounts. It exposes raw-data tools, a synthesis tool, and a methodology resource so users can list at-risk accounts or get a per-account health summary.

Scores companies against a configurable Ideal Customer Profile using firmographic and signal data. Returns a weighted fit score with per-criterion breakdowns.

Waterfall lead enrichment for AI agents. Cascades through Apollo, Clearbit, and Hunter to build the most complete lead profile in a single call.

A server for interacting with the Iaptic API, allowing AI models like Claude to query customer, purchase, and transaction data, as well as retrieve statistical insights.

Enables users to manage contacts, deals, follow-ups, activities, pipeline summaries, and outreach drafts stored in a local JSON file, with every write requiring an explicit preview and confirmation before it is applied. It operates without network access and never sends messages.