Version an agent-friendly API by keeping the existing contract stable, putting incompatible behavior behind an explicit new version or interface, and making every client’s selected version visible. For agents, compatibility includes more than valid JSON: schemas, descriptions, defaults, enum values, tool names, discovery results and the meaning of an operation all influence what the agent does.
Start with a contract, not a version number
An API is a contract between a provider and the code or agent that calls it. Google’s AIP-180 separates compatibility into three dimensions:
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- Source compatibility: existing client code still compiles or can be generated from the newer definition.
- Wire compatibility: requests and responses still encode and decode successfully.
- Semantic compatibility: the same inputs still mean the same thing and produce behavior the client expects.
An agent can pass wire validation while failing semantically. A response may remain valid JSON even though a changed default causes the model to act on only the first page of records, an enum acquires a value the prompt never anticipated, or a tool description now implies a different side effect. Treat all three dimensions as release criteria for every version.
AIP-180 puts the obligation plainly: users write code against APIs and expect it to keep working unless the stated stability level says otherwise. The same expectation applies to an agent that has already learned, cached or generated calls from your interface.
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What makes agent-facing compatibility different?
Tool schemas are executable guidance
Traditional clients usually bind to a specification through generated code or handwritten adapters. Agent clients may list tools, read JSON schemas and descriptions, then select an operation at runtime. Input constraints, required properties, examples, error shapes and natural-language descriptions therefore become operational inputs. Changing any of them can change tool selection or argument construction even when the HTTP endpoint and status codes remain unchanged.
Discovery can be cached
Agent wrappers and SDKs can discover tool definitions from a server. The OpenAI Agents SDK documentation describes listing MCP tools and optionally caching tool lists when definitions do not change often. A deployment that updates a schema but leaves cached definitions untouched can run two contracts at once: newly connected agents see one surface, while long-lived processes continue using another. Version plans must include cache refresh behavior, maximum staleness and a way to force rediscovery.
Names and descriptions are part of the interface
Keep a stable operation or tool name when its purpose and side effects remain stable. Renaming a tool, changing “preview” to “delete,” or weakening a constraint in prose can be as disruptive as changing a field type. If the meaning truly changes, expose a new name or versioned tool rather than silently repurposing the old one.
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Classify a proposed change before shipping it
Use this review table for every schema, documentation, validation or behavior change. “Same major version” means the change is safe only when the old contract’s behavior and meaning are preserved.
| Change | Compatibility risk | Safer treatment |
|---|---|---|
| Remove or rename an operation, parameter, response field or resource field | Breaking at source, wire or discovery level | Keep the old element through the transition; introduce a new version or operation |
| Change a field’s type or meaning | Existing serializers or agent reasoning can fail | Add a new field with explicit semantics, or use a new version |
| Make an optional request field required | Old requests are rejected | Retain the old default; require the field only in a new contract |
| Add validation that rejects previously accepted input | Previously successful calls become errors | Roll out warning-only validation first, then gate it by version |
| Change authentication or authorization requirements | Clients may lose access or expose new failure paths | Document credentials and permissions separately, with an explicit migration window |
| Change a default value or response shape | Old clients can infer the wrong result | Preserve the old default in the old version; make the new default explicit |
| Add a response field | Usually wire-compatible, but can break strict decoders or agent assumptions | Verify tolerant parsing and explain the field’s meaning; gate it if consumers treat responses as closed sets |
| Add a new response enum value | Clients that assume a closed set may misroute or fail | Document an unknown-value path and add values only where clients are designed to tolerate them |
Google AIP-180 permits many additive changes but warns against new required request fields, changed defaults and response enums that can grow unexpectedly. Its pagination example is especially important: if an endpoint previously returned every item and a new default page size is smaller, an old agent may believe a partial page is complete.
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Choose how clients select a version
There is no universal winner. Select one mechanism, document it consistently and make the selected value visible in generated examples, logs and support diagnostics.
| Mechanism | Advantages | Costs and risks | Best fit |
|---|---|---|---|
Major version in the URL path, such as /v2/ |
Visible in links, logs, traces and copied requests; easy to route | Resource URLs change; clients must update endpoint configuration | Whole-service contracts with clear incompatible releases |
| Version in an HTTP header | Resource URLs remain stable; can support date-based or interface versions | Tooling, caches and logs must preserve the header; copied URLs do not show the selected contract | Services that want stable resource URLs and explicit request metadata |
| Version in a query parameter | Easy to inspect and test; works where custom headers are inconvenient | Can leak into copied URLs, cache keys and analytics; omission behavior must be defined | Interface-level selection or transitional deployments |
| Interface or element-level versioning | Lets independent surfaces evolve without cloning an entire service | Requires stronger annotations, tooling, documentation and support discipline | Large APIs with separately owned interfaces |
Google’s traditional REST guidance places a major version in the URI for incompatible changes. AIP-185 also describes interface-based versioning through a header or query parameter, allowing callers to pin a supported interface version. GitHub’s REST API demonstrates header selection with X-GitHub-Api-Version. These are implementation examples, not a mandate to copy one provider’s scheme.
Make omission behavior explicit
Decide what happens when a caller sends no version. A safe policy is to keep an announced default for a defined period and return the selected version in response metadata or logs. Do not silently move unversioned traffic to a behavior that changes pagination, validation, authorization or tool meaning. GitHub warns that unversioned calls can observe behavior changes as older versions leave support; your policy should state the same risk in language clients can act on.
Keep old and new contracts separate
When behavior is incompatible, publish a new contract rather than adding hidden switches to the old one. The implementation can share internal code, but the externally visible schemas, defaults and error semantics must remain stable for callers that pinned the earlier version.
Version at the right boundary
- Service-wide major version: appropriate when authentication, resource modeling or many operations change together.
- Interface version: useful when one domain, such as billing or search, evolves independently.
- Operation or tool version: useful when one action’s side effects or input model changes while the surrounding interface remains stable.
- Capability negotiation: appropriate only when both sides can list capabilities, select one deterministically and fall back safely.
A negotiation protocol must never make the fallback ambiguous. Record the requested version, the selected version and the reason for any downgrade. For high-impact actions, require an explicit pin rather than letting an agent receive whichever version the server currently prefers.
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Separate preview from production
Do not label a changing preview as a stable contract. Google Compute Engine distinguishes stable versions, which retain strict compatibility expectations, from preview versions whose features may change or be removed. Mark preview tool schemas and endpoints clearly, give them an owner and an end date, and recommend stable client libraries for production integrations. A preview may be versioned, but its support promise must be visibly weaker than the promise attached to a stable version.
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Preserve request defaults
Never make an existing optional property required in place. If the old behavior inferred limit=100, keep that inference for the old version. In a new version, expose the new default in the schema, examples and response metadata so an agent can reason about it.
Handle additive response fields deliberately
Adding a response field is often wire-compatible, but not universally safe. Strict decoders may reject unknown properties, and an agent prompt may interpret a newly introduced field as authoritative. Publish whether clients must ignore unknown fields, and test representative older parsers. If a field changes the decision an agent should make, put that semantic change behind a version boundary rather than relying on additive JSON.
Plan for enum growth
Prefer an explicit unknown or “other” branch in client logic. Document whether enum values are open or closed. If an agent is expected to choose a tool based on an enum, include the action associated with each value and define what happens when the server returns a value introduced later.
Keep pagination semantics stable
Changing page size, cursor interpretation, sort order or the meaning of a “next” link can produce silent data loss. Preserve the old default and ordering in the old version. In a new version, state whether a response is complete, how to fetch subsequent pages and whether an empty page can still have a continuation token.
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Make errors machine-actionable
Keep stable error codes and distinguish retryable, authentication, validation and authorization failures. If the human message changes, do not assume the agent can infer the same recovery. A new error category or altered retry semantics belongs in migration notes and, when callers must change, in a new version.
Roll out a version without stranding agents
- Inventory consumers. Identify SDKs, direct HTTP clients, agent frameworks, MCP servers, generated schemas and long-running processes. Record which version each uses and whether tool definitions are cached.
- Write the compatibility decision. For every changed operation, field, default, enum, validation rule and permission, mark it additive, behavior-preserving or breaking. A breaking item must have a new version, interface or explicitly gated capability.
- Publish both contracts. Provide machine-readable schemas and human-readable descriptions for the old and new surfaces. Include representative requests, responses, errors, defaults and side effects.
- Make selection visible. Put the version in the URL, header or query parameter exactly as documented. Show it in generated client configuration, examples, access logs and traces.
- Refresh discovery safely. Document cache invalidation, maximum schema age and a forced-refresh method. Keep old tool definitions available while stale clients can still call them.
- Run dual contract tests. Send old client fixtures to the old version and new fixtures to the new version. Validate wire decoding, semantic results, pagination, enum handling, authorization and error recovery.
- Canary the new version. Start with low-risk consumers, compare outcomes and monitor version-specific error rates. Do not infer success from HTTP 2xx alone; inspect whether agents selected the intended operation and completed the intended task.
- Announce the migration window. State the release date, breaking changes, end of support, replacement version, required client updates and the process for exceptions.
- Measure usage by version. Track requests, active credentials, SDK versions, tool-list refreshes and failures. Contact owners of active old clients before retirement.
- Retire only after the announced date. Return deprecation and sunset metadata where appropriate, then remove the old contract after usage and risk review. Keep migration documentation available after shutdown.
Deprecation, sunset and support commitments
A deprecation notice should answer four questions: what is changing, which replacement to use, when support ends and what clients must do. The HTTP Deprecation and Sunset response headers can carry machine-readable signals, but they do not replace documentation or direct communication.
Support duration is a policy choice, not a universal constant. GitHub’s 2026 REST documentation states that a previous REST API version is supported for at least 24 months after a newer version is released. Treat that as GitHub’s commitment, not a default for every provider. Google AIP-185 asks APIs to coexist for a reasonable, well-communicated deprecation period and recommends 180 days for shutting down beta releases after deprecation in its release model. Choose a window based on client update cycles, agent deployment frequency, regulatory obligations and the severity of the change, then publish it before clients adopt the version.
Define exceptions. GitHub documents that critical security, data-exposure or severe reliability problems can lead to unscheduled versions and, rarely, a breaking change outside the ordinary cadence. Your own policy should describe the trigger, notification path, emergency mitigation and whether a temporary compatibility proxy will be offered.
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Contract tests
- Replay requests generated by the previous client schema against the supported old version.
- Validate required and optional properties, unknown-field handling, enum branches and numeric or string limits.
- Compare semantic results, not only status codes: records returned, side effects, authorization decisions and retry classification.
- Verify that old defaults remain unchanged and that new defaults appear only when the new version is selected.
Discovery tests
- Start an agent with a cached old tool list, deploy the new schema and confirm the old process continues to work.
- Force a refresh and verify that the new tool description, input schema and error documentation arrive together.
- Check that tool names remain unique and that descriptions do not contradict validation rules.
- Test a mixed fleet in which some agents negotiate a version and others pin one explicitly.
Operational checks
- Log requested and selected versions without exposing credentials or sensitive payloads.
- Alert on unversioned traffic, fallback negotiation, schema-refresh failures and calls after the sunset date.
- Keep dashboards split by version so a stable old contract does not hide failures in a new one.
Common failure modes and fixes
An additive field breaks a strict client
Symptom: an older decoder rejects otherwise valid responses. Fix by making old clients tolerant, suppressing the field for the old version, or moving the response shape to a new version. Do not claim that “additive” automatically means safe.
The agent stops after the first page
Symptom: summaries are incomplete after a pagination change. Fix by restoring the old page-size default, exposing continuation semantics in the schema and testing an agent that must follow the cursor until completion.
Cached tools call a retired operation
Symptom: newly started agents succeed while long-running workers receive unknown-tool or validation errors. Fix by publishing cache lifetime and refresh instructions, retaining the old definition during the transition and monitoring stale discovery traffic.
Negotiation silently downgrades
Symptom: a client requests a new capability but receives old behavior without noticing. Fix by returning the selected version explicitly, failing closed for high-impact operations and logging every fallback.
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Symptom: the model supplies arguments that prose permits but validation rejects, or chooses a tool for the wrong side effect. Fix by generating documentation from the same source where possible and adding review checks that compare names, required fields, enums, examples and error semantics.
A practical decision framework
Use these questions in order:
- Does the old request still validate? If not, the change is breaking.
- Does the old response still decode? If not, gate it or create a new version.
- Does the meaning, default, ordering or side effect change? If yes, treat it as semantic breakage even when JSON remains valid.
- Can an agent discover and cache the old surface? If yes, plan coexistence and refresh behavior.
- Can the client select and log a version deterministically? If not, fix selection before rollout.
- Is the change preview-only? Label it as preview and set a separate, shorter support promise.
If all answers support continuity, an additive change can remain in the same major contract. If any answer is negative, publish a new contract or an explicit capability gate and migrate consumers before retirement.
What a complete migration package contains
Give consumers one package they can implement without guessing:
- Old and new machine-readable schemas, with stable identifiers and version labels.
- A before-and-after table for operations, fields, defaults, enums, validation and authorization.
- Copyable requests and responses for success, pagination, validation, authentication and authorization failures.
- Tool descriptions that state side effects, idempotency, required confirmation and retry safety.
- Client configuration showing the exact path, header or query parameter used to select the version.
- Discovery-cache instructions, including refresh triggers and maximum acceptable staleness.
- Support dates, deprecation and sunset signals, monitoring contacts and emergency exceptions.
- Contract-test fixtures that consumers can run before switching production traffic.
Stripe’s 2017 API-versioning account said its API had remained compatible with every version since the company’s 2011 inception. That is a company-reported historical statement, not a universal target, but it illustrates the value of treating compatibility as an ongoing product capability rather than a one-time URL decision.
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Bottom line for API owners
Keep stable versions boring: preserve defaults, accepted inputs, response meaning, tool names and side effects. Put incompatible changes behind a version or interface that callers explicitly select. Publish schemas and migration examples, account for cached agent discovery, test semantic behavior with older clients, expose deprecation and sunset dates, and retire only after the announced window. That discipline lets agents evolve without forcing every existing deployment to change on the same day.
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