Best AI Agent Builders for Model Context Protocol (MCP)

Postman serves as a collaborative platform for developing APIs, designed to simplify the entire process of API creation and enhance teamwork, enabling the rapid development of superior APIs. The platform's features facilitate each phase of API construction, making it easier to collaborate and accelerate the creation of high-quality APIs. Users can quickly and effortlessly send requests for REST, SOAP, and GraphQL directly within Postman, optimizing their workflow. Additionally, it allows for the automation of manual tests, seamlessly integrating them into your CI/CD pipeline to safeguard against potential issues when code changes are deployed to production. API behavior can be communicated effectively by simulating endpoints and their respective responses without the need for a backend server setup. You can also generate and publish visually appealing, machine-readable documentation, which helps in making your API more accessible for users. Regular performance and response time checks ensure you stay informed about your API's health, allowing for proactive management. Lastly, Postman fosters a shared environment for API creation and consumption, enabling real-time collaboration among team members. Postman’s AI Agent Builder revolutionizes the development of AI agents with its no-code platform, enabling users to build, test, and deploy powerful agents without coding expertise. It provides access to a vast library of over 100,000 APIs and a variety of LLMs, offering tools to compare their performance, cost, and response quality. The visual workflow builder simplifies creating multi-step agent interactions, and its testing tools ensure reliability before deployment.

Metaflow serves as an intuitive agent creator and automation framework for growth operators and knowledge professionals who find themselves constrained by inflexible app connections and a plethora of prompt threads. This platform allows for uninhibited ideation while transforming insights into scalable AI workflows seamlessly. In contrast to conventional automation solutions that compartmentalize creativity from implementation, Metaflow integrates both discovery and execution into a cohesive environment. This integration facilitates exploration, development, and maturation of ideas into robust systems that generate significant impact. As a result, growth teams can liberate their cognitive resources, enabling them to engage in work that is profoundly fulfilling and impactful. Ultimately, Metaflow empowers users to harness their creativity while also streamlining their operational processes.

Runbear empowers teams to rapidly build AI-powered agents without any coding, seamlessly integrating them into widely used communication platforms such as Slack, Teams, Discord, and HubSpot. The platform enables users to deploy specialized AI assistants connected to models like OpenAI, Claude, and Gemini, enhanced by integrations with knowledge sources including Google Drive, Notion, and Confluence to keep content updated automatically. Runbear’s flexible multi-agent management lets organizations customize AI experiences for different teams, improving productivity and collaboration across departments. Key features include automating meeting prep, generating PRDs from Slack threads, querying databases with natural language, and triggering workflow automation through Zapier—all directly from chat environments. The product is designed to simplify complex workflows by reducing repetitive tasks and providing instant, context-aware AI responses to common questions. Companies across various industries praise Runbear for its intuitive interface, seamless setup, and transformative impact on team communication and efficiency. Additionally, Runbear supports compliance with enterprise-grade security standards such as SOC2. This makes it a reliable choice for businesses looking to incorporate AI assistants while maintaining data integrity and privacy.

Mastra is an open-source TypeScript framework that allows developers to build AI agents capable of performing tasks, managing knowledge, and retaining memory across interactions. With a clean and intuitive API, Mastra simplifies the creation of complex agent workflows, enabling real-time task execution and seamless integration with machine learning models like GPT-4. The framework supports task orchestration, agent memory, and knowledge management, making it ideal for applications in automation, personalized services, and complex systems.

Portia AI is an open-source developer framework that includes optional cloud services, enabling teams to quickly create, deploy, and oversee stateful, authenticated AI agents while maintaining full visibility and control over the process. Developers initiate the process by using the SDK to generate clear, organized multi-step "plans" that integrate LLM reasoning with various tool calls, executing these plans incrementally and enhancing the plan state at each step, while also allowing for pauses to seek clarifications, whether from human users or machine inputs, when authentication or additional information is necessary. With its cohesive authentication framework and an easily customizable tool catalog, Portia automatically manages the credentials and permissions needed for remote API and MCP tool calls. Furthermore, the accompanying cloud solution provides persistent storage for plan execution states, historical log tracking, telemetry dashboards, and managed scaling, ensuring that production deployments remain dependable, traceable, and compliant with regulatory standards. This comprehensive approach not only simplifies the development process but also enhances the overall efficiency and effectiveness of AI agent deployments.

Koog is a Kotlin-based framework designed for developing and executing AI agents using idiomatic Kotlin, catering to both simple agents that handle individual inputs and more intricate workflow agents with tailored strategies and configurations. Its architecture is built entirely in Kotlin, ensuring a smooth integration of the Model Control Protocol (MCP) for improved management of models. The framework also utilizes vector embeddings to facilitate semantic search and offers a versatile system for creating and enhancing tools that can interact with external systems and APIs. Components that are ready for immediate use tackle prevalent challenges in AI engineering, while intelligent history compression techniques are employed to optimize token consumption and maintain context. Additionally, a robust streaming API supports real-time response processing and allows for simultaneous tool invocations. Agents benefit from persistent memory, which enables them to retain knowledge across different sessions and among various agents, and detailed tracing facilities enhance the debugging and monitoring process, ensuring developers have the insights needed for effective optimization. This combination of features positions Koog as a comprehensive solution for developers looking to harness the power of AI in their applications.

MCP-Use is an open-source platform designed for developers that provides an array of SDKs, cloud infrastructure, and an intuitive control interface to facilitate the creation, management, and deployment of AI agents utilizing the Model Context Protocol (MCP). The platform allows connections to various MCP servers, each offering distinct tool functionalities such as web browsing, file handling, or specialized third-party integrations, all accessible through a single, unified MCPClient. Developers are empowered to build custom agents (using MCPAgent) that can intelligently choose the most suitable server for each specific task by leveraging configurable pipelines or a built-in server management system. By streamlining processes like authentication, managing access control, audit logging, observability, and creating sandboxed runtime environments, it ensures that both self-hosted and managed MCP developments are primed for production use. Moreover, MCP-Use enhances the development experience by integrating with well-known frameworks such as LangChain (Python) and LangChain.js (TypeScript), significantly speeding up the process of building AI agents equipped with diverse tools. In addition, its user-friendly architecture encourages developers to innovate and experiment with new AI functionalities more efficiently.

The fastest way to integrate APIs, and run code. Pipedream is a serverless computing platform and integration platform that makes it easy for developers to create event-driven workflows and connect apps. Any API can be turned into an event stream by creating event sources. You can create event sources to listen for tweets, Github events or Airtable records. You can inspect events in a human-friendly manner, trigger Node.js workflows for every event, and consume events in your app via API. Node.js code steps are used to create workflows that run on every event. You can write your own Node.js and use any npm packages. Or you can reuse actions that scaffold popular APIs. You can trigger via sources, a custom URL, email address or SDK code, or a schedule. Connect to Auth apps once and they will continue to work in your workflow. Pipedream supports OAuth, key-based auth and handles token refresh and OAuth flow for you. Simply link accounts to steps, and include the appropriate auth information in code.

Azure AI Foundry serves as a comprehensive application platform tailored for organizations navigating the AI landscape. By connecting advanced AI technologies with real-world business needs, Azure AI Foundry enables companies to fully leverage AI capabilities in a streamlined manner. This platform is specifically crafted to empower every member of an organization—ranging from developers and AI engineers to IT specialists—allowing them to easily customize, host, execute, and oversee AI solutions. Through this cohesive strategy, the development and management processes are significantly streamlined, allowing all participants to concentrate on fostering innovation and realizing their strategic objectives effectively. In doing so, Azure AI Foundry not only enhances individual productivity but also promotes collaborative efforts across various teams. Azure AI Foundry Agent Service provides a comprehensive solution for managing AI agents from the beginning to the end of their lifecycle. This powerful tool allows for smooth development, deployment, and production, ensuring that AI agents perform optimally at every stage. The service simplifies the management process, making it easier to track and optimize AI operations while minimizing potential issues in the lifecycle.