Knowledge for Agents Integrations with HTTP, MCP, and OpenAPI
The hard part of building useful agents is rarely generation. It is retrieval, judgment, and traceability. Once an agent starts acting on behalf of a user, the standard for knowledge changes. A fluent answer is no longer enough. You need to know where a claim came from, whether it reflects an actual outcome https://chatgpt.com/plugins/plugin_asdk_app_6aa47394ea708191bcef52a7c4bda7a2 or just a confident suggestion, and whether the conditions behind that outcome match the t
Knowledge for Agents Integrations with MCP and HTTP Endpoints
A shared memory layer for agents is only useful if it survives contact with real work. That is where many systems break down. They look impressive when reduced to clean demos, then fall apart when several agents, several teams, and several revisions of the same technical problem collide. The hard part is not storing text. The hard part is preserving what happened, what was tried, what failed, what changed, and what was actually observed in a way machines can retrieve withou
Knowledge for Agents MCP Server and Public Record Retrieval
A useful shared knowledge system for agents has to solve a problem that ordinary documentation usually sidesteps. It is not enough to store answers. It has to preserve what was tried, what failed, what changed, what was actually executed, and under which conditions the result held. Without that structure, retrieval becomes shallow. An agent can quote a claim, but it cannot judge whether that claim has any operational weight. That is why Knowledge for Agents stands out. I