Koa Fhe
Let an agent orchestrate fully homomorphic encryption workloads so sensitive values stay encrypted on the server side.
Overview
koa-fhe is a MCP server for the Build phase that runs fully homomorphic encryption compute so the server processes encrypted data without accessing plaintext.
What is this MCP server?
- Confidential coprocessor MCP: compute on ciphertext without server seeing plaintext
- PyPI package identifier koa-fhe at version 0.1.2
- stdio transport for agent-driven FHE workflows
- GitHub repository Euda1mon1a/koa-fhe as the integration source
- Early-stage server (0.1.x) suited to prototypes and privacy-sensitive features
- Published MCP server version 0.1.2
- Transport type stdio per server.schema.json
What problem does it solve?
You need agent-assisted computation on sensitive values but cannot let the service provider or MCP host see decrypted inputs.
Who is it for?
Builders prototyping privacy-preserving APIs or agent workflows where FHE-backed compute is already part of the architecture.
Skip if: Typical CRUD apps, quick MVPs without compliance pressure, or anyone who needs beginner-friendly crypto with minimal setup.
What do I get? / Deliverables
Your agent calls FHE coprocessor tools over MCP while ciphertext stays on the confidential compute path the server advertises.
- stdio MCP bridge to the koa-fhe confidential coprocessor
- Agent-callable encrypted compute workflow without server-side plaintext
- Foundation to embed FHE-backed features in a privacy-sensitive backend
Recommended MCP Servers
Journey fit
Koa FHE lands in Build when you are wiring confidential compute into APIs or agent-driven backends, not when you are only doing market research. It is a backend coprocessor integration exposed as MCP over stdio via the PyPI koa-fhe package, aimed at encrypted compute paths.
How it compares
FHE confidential coprocessor MCP integration, not a secrets vault or static PII redaction skill.
Common Questions / FAQ
Who is koa-fhe for?
Developers and solo builders adding encrypted-data compute to backends who want MCP agents to drive FHE operations instead of custom CLIs alone.
When should I use koa-fhe?
Use it in Build when your backend design requires computation on ciphertext and you are wiring that path into an AI coding agent workflow.
How do I add koa-fhe to my agent?
Install the koa-fhe PyPI package, configure a stdio MCP server entry pointing at that runtime, and reconnect your MCP-enabled editor or agent client.