synapse-adapter-sdk 0.1.1

The intelligence layer above the AI protocol layer — canonical IR and adapter framework for heterogeneous AI model pipelines

SYNAPSE Adapter SDK

SYNAPSE is a canonical intermediate representation (IR) protocol that lets AI models with incompatible schemas interoperate through a unified adapter interface.

Write two functions — connect your AI model to every other model in the ecosystem.

Without SYNAPSE: 4 models require 6 custom connectors. 10 models require 45. Each breaks when either model's schema changes.

With SYNAPSE: write one ingress and one egress adapter. Done. Your model is immediately composable with every other registered model.

Install

pip install synapse-adapter-sdk

Write your first adapter

from synapse_sdk import AdapterBase, CanonicalIR, ProvenanceEntry
from typing import Any

class MyModelAdapter(AdapterBase):
    MODEL_ID = "my-org/my-model-v1.0"
    ADAPTER_VERSION = "1.0.0"

    def ingress(self, ir: CanonicalIR) -> dict[str, Any]:
        return { "input": ir.payload.content }

    def egress(self, output: dict, original_ir: CanonicalIR, latency_ms: int) -> CanonicalIR:
        updated = original_ir.copy()
        updated.provenance.append(self.build_provenance(
            confidence=output["score"],
            latency_ms=latency_ms,
        ))
        return updated

Validate

synapse-validate --adapter my_module.MyModelAdapter

Documentation

• Getting started
• Writing adapters
• Canonical IR specification
• Registry

What SYNAPSE is not

SYNAPSE does not compete with MCP or A2A. It builds on top of them. MCP connects agents to tools. A2A connects agents to each other. SYNAPSE connects specialized models with incompatible schemas — and makes routing between them smarter over time.

License

MIT. See LICENSE.