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Connect Hermes Agent to read and write learning loop data via API.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "hermes-platform-mcp" yet — see the docs or source repo.
Using hermes-platform-mcp, write this user feedback to Hermes Intelligence Platform: task ID=task-1024, feedback="The answer was accurate but lacked examples," and link it to the current session context.
The tool writes the feedback and related context to the platform for later learning-loop use.
Use hermes-platform-mcp to read historical memory, signals, and context related to the current user session, then summarize them briefly.
It returns a summary of relevant learning-loop data to help the agent continue the context.
Through hermes-platform-mcp, write the new context and key observations from this interaction to the Hermes platform, including goals, outcomes, and anomaly signals.
The platform’s learning-loop record is updated with this interaction’s context and signals.
Developers building a Hermes Agent can use it to connect to the platform API over stdio and read or write context, feedback, signals, and memory. This lets the agent feed interaction results into a learning loop.
When an agent needs to save feedback or retrieve past memory after a task, this MCP tool acts as the bridge to Hermes Intelligence Platform. It fits workflows that require continuity and accumulated experience.
It connects Hermes Agent to the Hermes Intelligence Platform API and exposes read/write access over stdio for learning-loop data such as context, feedback, signals, and memory.
From the provided information, it depends on the Hermes Intelligence Platform API and works over stdio. For exact installation, authentication, or runtime requirements, see the source repository.
The available information shows it is an MCP bridge for Hermes Agent, focused on letting the agent access learning-loop data over stdio. For finer architectural differences, see the source repository.
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