Merge Agent Handler

Merge is a connective infrastructure platform and universal context engine for AI agents, developed for companies building internal and customer-facing AI products. It connects agents to company data, tools, and models, with capabilities for authenticated tool access, LLM routing, customer-data synchronization, workforce access control, shared skills, and security auditing. Its context-layer approach combines synchronized copies of large datasets with live API lookups. A router selects between cached or live context, a summarizer derives higher-level context, and company skills and memory encode organizational definitions and procedures. The system also tracks data provenance, including where context came from and when it may become invalid.

Composio MCP Gateway is a governed MCP gateway for connecting AI agents to Composio's managed tools and customer-provided MCP servers. It provides a centralized endpoint through which agents discover and call tools across services such as Slack, Sentry, Datadog, PostHog, and Metabase, instead of connecting separately to each application. The gateway applies organization, team, user, and action-level access policies; keeps credentials out of agent configuration; manages authentication and token refresh; and records tool calls in a shared audit trail. Composio describes it as supporting more than 1,500 managed integrations and production use by enterprise teams.

An MCP server from Zapier that connects authenticated applications so compatible AI tools can access and use them through a single integration layer. It supports clients including Cursor, Claude Code, and Codex.

AgentConnect is an open-source, self-hostable platform that integrates autonomous AI agents (ACP agents such as Claude Code, Codex, and Gemini CLI) into communication platforms including Slack, Telegram, Discord, and GitHub. It provides tagging of agents and facilities to assign roles, tools, and memory so agents can act within those channels.

Model Context Protocol (MCP) is an open, standardized protocol layer for connecting large language models and AI agents with external data sources, hosted infrastructure tools, and other contextual data. It defines formats, metadata, protocol schemas, and APIs for sharing information and tools, attaching, referencing, and validating context such as documents, embeddings, and provenance, while supporting scoped authentication and permissions. MCP translates JSON requests from an agent into calls to service APIs, including CRM, container-management, and GKE capabilities, and can provide design-system context and related tools for generating consistent applications. The official project publishes its specification, documentation, and protocol schema; the schema is defined first in TypeScript and also provided as JSON Schema for broader compatibility. The protocol was created by David Soria Parra and Justin Spahr-Summers, is hosted at modelcontextprotocol.io, and is licensed under the MIT License.