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.
pip install synapse-adapter-sdkfrom 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 updatedsynapse-validate --adapter my_module.MyModelAdapterSYNAPSE 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.
MIT. See LICENSE.