Osmp
Wire efficient, inference-free agent instruction payloads into MCP clients instead of verbose JSON over any transport channel.
Overview
io.github.Octid-io/osmp is a MCP server for the Build phase that encodes and decodes agentic AI instructions more compactly than JSON with inference-free decode for any channel.
What is this MCP server?
- Claims ~86.8% size or efficiency advantage versus JSON for agentic instruction payloads
- Inference-free decode so agents can read instructions without an extra model pass
- stdio MCP via PyPI package osmp-mcp (versions 1.3.3 and 1.3.4 listed)
- Designed for any channel—stdio and broader agent comms, not one SaaS API
- Open-source repo octid-io/cloudless-sky on GitHub
- Project cites ~86.8% efficiency versus JSON for agentic instruction encoding
- Two PyPI package entries listed at versions 1.3.3 and 1.3.4 with stdio transport
- Server schema version field 1.3.3 in catalog metadata
Community signal: 5 GitHub stars.
What problem does it solve?
Agent instruction and tool payloads in JSON eat context, add decode cost, and get awkward when you chain multiple agents or channels.
Who is it for?
Indie builders building multi-tool agent stacks who need a standardized, efficient instruction wire format inside MCP.
Skip if: Builders who only need occasional REST calls or who are not yet running MCP-linked agents locally.
What do I get? / Deliverables
After you register osmp-mcp over stdio, agents can exchange slimmer instruction blobs that decode deterministically without an extra inference step.
- Registered stdio MCP server using osmp-mcp
- Encoded agent instruction streams decodable without an extra model inference pass
- Reusable instruction format across agent channels you configure
Recommended MCP Servers
Journey fit
Canonical shelf is Build because the server exists to encode and decode agent instructions while you design agent pipelines and tool wiring. Agent-tooling is the best fit: OSMP is a transport/encoding layer for agentic instructions, not a standalone product feature.
How it compares
Instruction-encoding MCP transport, not a planning skill or hosted LLM API.
Common Questions / FAQ
Who is io.github.Octid-io/osmp for?
Solo and small-team developers wiring Claude Code, Cursor, or Codex to custom MCP servers who want leaner agent instruction payloads than raw JSON.
When should I use io.github.Octid-io/osmp?
Use it while building or hardening agent pipelines when context size, decode latency, or cross-channel instruction sync becomes a bottleneck.
How do I add io.github.Octid-io/osmp to my agent?
Install the PyPI package osmp-mcp, configure stdio transport in your MCP client, and point the server entry at the published osmp-mcp identifier for your chosen version.