Strata's MCP dream is scalable AI tool use in the real world. The open-source Strata MCP server from Klavis AI lets AI agents wield thousands of API tools without getting overwhelmed. It reveals tools step-by-step, based on what the AI actually needs. [1]
That progressive, human-like discovery unlocks deep tool access (think GitHub, Jira, Slack) with tokens and docs managed in the background. [1]
On the other side, FieldFlow turns any REST API into a GraphQL-like API with per-endpoint field selection from an OpenAPI spec. A one-command setup builds a FieldFlow-optimized MCP server so AI agents fetch only the needed fields, reducing noise and speeding responses. [2]
Benchmarks and ops notes follow the same thread: Strata on the MCPMark leaderboard shows +15.2% higher pass@1 vs the official GitHub server and +13.4% vs the official Notion server. Under the hood, Strata manages authentication tokens and includes a built-in search tool for the agent to read documentation if needed. [1]
Enterprise implications look bright: a single open-source MCP hub can coordinate thousands of granular features across GitHub, Jira, Slack, and more, while FieldFlow keeps context lean for faster, multi-provider setups. [1][2]
Closing thought: these pieces signal a path to scalable, enterprise-grade LLM tooling that blends deep tool access with lean context management.
References
Launch HN: Strata (YC X25) – One MCP server for AI to handle thousands of tools
Open-source Strata guides LLMs through categories and actions, enabling scalable tool use, with benchmarks, security talk, and enterprise questions discussion.
View sourceShow HN: Transform your REST API into optimized MCP server in one command line
Open-source tool converts REST to field-selective API, reducing context noise for AI agents and speeding LLM responses overall.
View source