AI agent integration platform
Legacy APIs weren’t built for agents.
Hundreds of versions. Incomplete specs. Sequences nobody wrote down. Your agent is expected to call a vendor API correctly on the first try, using documentation that was wrong before it was published.
Swytchcode is an AI agent integration platform. It helps your team find the right API path for the business workflows you need to run, then governs how each agent action runs in production—with authentication, retries, idempotency, validation, and auditability built in.
Use the LLM your team prefers. Start free with MCP and CLI—without a separate SDK for every service.
The requirement
What an AI agent integration platform has to do
An agent that can reason about a task still has to execute it against a real system. Between the model's decision and the vendor's endpoint sit four problems that a prompt cannot solve.
Find the right path
One operation can accept more valid field combinations than anyone documented, across years of overlapping versions. Knowing an endpoint exists is not the same as knowing which call your workflow needs.
Prove the call is correct before it goes out
Schema validation against the live contract, not against what a model learned during training.
Decide whether the action is allowed to run at all
Allowlists, environment boundaries, dry runs. A destructive call against production instead of test should be stopped, not logged after the fact.
Know what actually happened
A 200 response with an error in the body is a failure your agent will record as a success. Retries without idempotency turn one intended action into three real ones.
A platform that handles the first problem is a catalog. A platform that handles all four is a runtime.
The mechanism
Where the implementation knowledge comes from
- 01
Ingest
The API’s specification, SDKs, and documentation.
- 02
Correct
Published specs are frequently wrong. Raw ingestion is not enough, so the spec is reconciled against how the API actually behaves.
- 03
Codify
Every failure encountered gets fixed and written into the system permanently. The next team never hits it.
- 04
Compile
The corrected result becomes a manifest—a condensed, accurate contract paired with the documentation knowledge the vendor never published.
- 05
Serve
Your agent receives the exact methods its workflow needs through MCP, rather than being handed the entire API surface.
In production
What runs in production
| Capability | What it prevents |
|---|---|
| Authentication | Credentials in agent code or prompts. Tokens resolved at execution, never held by the model. |
| Retries with idempotency | One intended action becoming three real ones when a call is retried. |
| Schema and response validation | Malformed payloads going out, and error-carrying 200s being recorded as success. |
| Policy control | Destructive or out-of-scope calls executing. Allowlists and environment boundaries enforced before the call. |
| Auditability | An action nobody can reconstruct afterward. Every call recorded. |
Who it’s for
Who it’s for
Engineering teams moving agents from working demos into production against systems they do not own—vendor APIs, and the internal APIs that behave like them.
The pattern is consistent: the agent logic is fine, the prompts are fine, and the integration layer is where it breaks.
Getting started
How teams get started
- 01
Install the CLI in one command
No SDK setup.
- 02
Pull the manifest for the API your workflow needs
Correct methods, correct versions.
- 03
Execute with validation and audit
Policy enforced before anything runs.
FAQ