Example workflows you can create to give prospects, customers and team members helpful experiences.
Identify companies hiring for relevant roles, enrich contacts, and send targeted outreach emails.
Identify companies using complementary or competing tech, then pitch an alternative or add-on solution.
Monitor social platforms for pain points, respond with helpful info, and reach out personally.
Compile a prioritized list of contacts and enrich them with key details for more effective outreach.
Automatically deliver relevant drip campaigns with AI-curated content and adaptive timing to move leads through the funnel.
Execute a multi-channel, hyper-personalized ABM outreach sequence using AI and automation to engage target prospects.
Categorize and rank target accounts by tier using AI-driven data to prioritize outreach and resources.
Re-engage lapsed customers or prospects using AI-driven insights to personalize outreach and tailored win-back offers.
Automatically enriches new lead data, qualifies and routes leads via CRM rules, alerts sales with summaries, and tags non-qualified leads for nurture.
Compiles customer usage data, generates AI-powered business review summaries, and creates visually engaging QBR reports with minimal manual effort.
Aggregates feedback from multiple channels, uses AI to categorize into themes, and generates actionable reports with key sentiment insights.
Automatically sends personalized follow-up emails based on customer survey scores, addressing detractors with urgent outreach and engaging promoters for advocacy.
Building-block agents you can create to give reusable capabilities to your agents.
A base pattern agent for planning B2B projects. It extracts key planning details from user conversations, checks for relevance, and then leverages planning tools to generate a complete project plan.
Conduct iterative deep research on a topic by generating queries, summarizing web results, reflecting on gaps, and finalizing insights.
A supervisor/orchestrator agent that listens to user chat, routes the conversation to the appropriate tool, and then calls the chosen agent.
Example agents you can create that interact with other agents (yours or 3rd parties) using the Agent-To-Agent protocol.
Your agent engages with a remote (possibly 3rd-party) agent via the A2A protocol.
Orchestrate communication between a user and multiple remote A2A agents via a central orchestrator agent using the A2A protocol.
Example MCPs you can create to give your AI apps and third-party AI apps access to your product's features.
MCP server for authenticated customers to access and operate product's core functionality, including account management, service operations, and real-time analytics.
MCP server for customers to get support for your products and services.
MCP server for authenticated team members to read, create, and update internal documentation via AI agents.
MCP server for agents to query product information and return product details, features, integrations, multimedia assets and other relevant information.
Existing MCPs you can configure to give your Ai apps access to 3rd-party tools.
MCP server integrating Brave Search API for web and local search capabilities.
MCP server for retrieving web content and converting HTML to markdown for LLM consumption.
MCP server for GitHub API integration, supporting repository management and file operations.
MCP server integrating Google Drive, allowing listing, reading, and searching files via LLMs.
MCP server for Google Maps services, providing location search and directions via Maps API.
MCP server implementing a persistent memory system using a local knowledge graph. Optionally define where to store the minimal JSON graph.
MCP server enabling read-only PostgreSQL database access with schema inspection via LLMs.
MCP server providing browser automation and web scraping capabilities using Puppeteer.
MCP server integration for Sentry.io, retrieving and analyzing issue data from Sentry projects.
MCP server providing a tool for dynamic, structured problem-solving via sequential thought processes.
MCP server for Chroma, providing embeddings, vector search, document storage, and full-text search via the open-source Chroma vector database.
MCP server for Exa, a search engine designed for AI, allowing AI agents to perform web search through Exa’s API.
MCP server for Inkeep that enables Retrieval-Augmented Generation (RAG) searches over a user’s content via Inkeep’s platform.
MCP server that allows AI agents to perform web searches using the Kagi search API, returning results for use in conversations.
Production-ready RAG (Retrieval Augmented Generation) MCP server that lets AI search and retrieve data from documents out-of-the-box.
GitHub’s official MCP server, allowing AI assistants to interact with GitHub (repositories, issues, PRs, etc.) through standardized function calls.
MCP server for Aiven cloud platform, providing natural language access to Aiven projects and services (PostgreSQL, Kafka, ClickHouse, OpenSearch).
MCP server for ClickHouse that lets AI assistants query a ClickHouse database using natural language.
MCP server built into Convex’s CLI (Convex 1.19.5), allowing AI agents to introspect Convex deployments, call functions, and read/write data via safe sandboxed queries.
MCP server for GreptimeDB that provides a secure interface for AI assistants to explore and analyze time-series data in GreptimeDB.
Open-source MCP server offering easy, fast, and secure tool access for databases (a suite of DB tools via MCP).
MCP server for Milvus vector database, enabling AI agents to search and query vector data in a Milvus DB using natural language.
MCP server for MotherDuck (DuckDB-as-a-service), allowing AI to query and analyze data in MotherDuck and local DuckDB seamlessly.
MCP server for Neo4j graph database providing schema insights and read/write Cypher query capabilities, plus a graph-backed memory.
MCP server for the Neon serverless Postgres platform, enabling AI assistants to interact with Neon databases using natural language.
MCP server for OceanBase, enabling AI to interact with OceanBase database instances and tooling via the MCP interface.
MCP server that automates browser interactions in the cloud (web navigation, data extraction, form filling, etc).
MCP server for Hyperbrowser (AI browser automation platform), empowering AI agents with scalable browser automation capabilities.
MCP server that enables AI agents to extract structured data from unstructured web content using AgentQL.
Official MCP server for Apify Actors, allowing AI agents to run 3,000+ pre-built cloud automation and web scraping tools via Apify’s API.
MCP server for Firecrawl, allowing AI agents to extract web data and crawl websites for information via Firecrawl’s tools.
MCP server that integrates with Oxylabs’ Web Scraping API, supporting dynamic rendering and parsing to extract structured data from websites.
MCP server for Opik (by Comet) that allows AI agents to query and analyze logged data (logs, traces, prompts) from Opik in natural language.
MCP server for Grafana that lets AI agents search dashboards, investigate incidents, and query data sources in a Grafana instance.
MCP server for 21st.dev’s Magic tool, which generates UI components from natural language descriptions.
Universal RPC layer MCP server allowing AI agents to call any function in any language across network boundaries.
MCP server by APIMatic that processes OpenAPI files and returns validation summaries using APIMatic’s API.
MCP server enabling AI agents to interact with Audiense Insights for demographic, cultural, influencer, and content engagement analysis.
MCP server for Axiom that lets AI agents query and analyze logs, traces, and other event data in natural language.
Official MCP server for Box, allowing AI assistants to interact with Box’s content management platform (files, folders, etc) via Box AI.
MCP server for Bucket, enabling feature flagging, company data management, and feature access control via AI agents.
MCP server that connects AI agents to the Chargebee platform, allowing them to manage subscriptions, invoices, and billing via Chargebee’s API.
MCP server that connects to Chronulus AI to provide forecasting and prediction agents capable of predicting anything.
Official MCP server for CircleCI, allowing AI agents to identify and fix build failures and interact with CI pipelines.
MCP server for Cloudflare’s developer platform, enabling deployment, configuration, and interrogation of resources (Workers, KV, R2, D1) via AI.
MCP server for Dart (the AI-native project management tool), enabling AI to interact with tasks, docs, and project data on the platform.
MCP server for the DevHub CMS, allowing AI assistants to manage and utilize website content within the DevHub platform.
MCP server for E2B that allows AI agents to run code in secure sandboxes hosted by E2B.
MCP server for EduBase, enabling AI to interact with EduBase’s e-learning platform (quizzes, exams, content organization) via MCP.
MCP server for Element.fm, enabling AI agents to create and publish unlimited podcast shows and episodes through the platform.
MCP server enabling AI agents to securely initiate purchases using Fewsats, a platform facilitating small payments (satoshis).
MCP server for Fibery that allows AI agents to perform queries and operate on entities in a Fibery workspace (no-code work management platform).
MCP server for gotoHuman (a human-in-the-loop platform), enabling AI automations to send approval requests to a human inbox.
MCP server that provides a sandboxed Python execution environment (ForeverVM) for AI agents to run Python code safely.
MCP server that allows AI agents to interact with various other SaaS applications on behalf of users, acting as an integration hub.
MCP server that brings real-time production context (logs, metrics, traces) into the AI environment to help auto-fix code faster (observability integration).
MCP server providing access to OpenTelemetry traces and metrics through the Logfire platform, so AI can analyze telemetry data.
Open-source prompt management MCP server by Langfuse, allowing collaborative editing, versioning, evaluation, and release of prompts via MCP.
MCP server for Mailgun that allows AI agents to send, receive, and manage emails via the Mailgun Email API.
MCP server integrating with the Mailtrap Email API, so AI assistants can send and test emails using Mailtrap’s sandbox service.
MCP server for Make.com that turns user-defined automation scenarios into callable tools for AI assistants.
Client implementation for Mastra that provides seamless integration with MCP-compatible AI models and tools.
MCP server providing AI assistants with direct access to Mastra.ai’s complete knowledge base and documentation.
Official Notion MCP server that allows AI agents to interact with Notion (the productivity/workspace app) via MCP calls.
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