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Use an explicit, stable contract for every released API version, put incompatible behavior behind a new version or interface, and let each agent pin or negotiate the contract it understands. For agent-facing APIs, backward compatibility includes more than valid JSON: operation names, tool descriptions, defaults, enum meanings, validation rules, discovery results and error semantics can all change an agent’s decision even when a parser reports success. Keep old and new contracts live during a declared migration window, publish machine-readable schemas and before/after examples, expose deprecation dates, and test representative older agent schemas before retiring anything.
What compatibility means for an agent
Google AIP-180 separates compatibility into three dimensions: source, wire and semantic compatibility. Source compatibility means existing client code still builds or runs. Wire compatibility means requests and responses can still be encoded and decoded. Semantic compatibility means the same fields, defaults and operations still mean the same thing. The distinction matters most for agents: a model can parse a response perfectly yet choose the wrong action because a description, default or enum meaning changed.
AIP-180 frames an API as a contract that users expect to keep working in production unless its stated stability level says otherwise. The guidance is written primarily for protobuf and JSON APIs; other transports have their own details, but the contract principle remains useful.
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Source compatibility
Do not remove or rename an operation, parameter, response field or resource field that existing generated clients reference. Changing a field type can break code generation, deserialization or validation even when the new type appears logically similar. Treat authentication and authorization requirements as part of source compatibility too: a client that previously succeeded must not suddenly need a new scope or credential without a versioned migration.
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Wire compatibility
Keep the existing request and response shape readable by clients of the same major version. Never turn an optional request property into a required one for an existing version. Preserve server-populated fields and prior defaults. A response enum that gains new values can also break clients that assume a closed set; consumers should use an unknown-value branch, while producers should document the possibility before adding values.
Semantic compatibility
Semantic breaks are particularly easy to miss in agent systems. Changing mode: "safe" so it now permits an action that was previously blocked, narrowing a search default, or changing the meaning of a tool description can alter model behavior without invalidating JSON. Stable operation names, precise descriptions, examples, error meanings and defaults are therefore contract elements, not editorial decoration.
Which changes are breaking?
Use a compatibility review for every release, not only for obvious endpoint removals. The following changes should normally require a new major version, a version-gated interface, or an explicitly coordinated migration:
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- Changing a field type, units, interpretation or allowed range.
- Making a previously optional request parameter mandatory.
- Adding validation that rejects inputs the old contract accepted.
- Changing authentication, authorization, scopes or required headers.
- Changing a default, response shape or error behavior so an old client infers a different result.
- Changing an operation name, tool description or capability declaration in a way that can cause an agent to select another action.
Additions need review as well. A new optional response field is often wire-compatible, but a new request requirement is not. A smaller default page size is a semantic break even though pagination still works: an older agent that expected one complete result may treat the first page as the full answer. New response-enum values can surprise clients that branch on an assumed closed list. Preserve prior behavior by default and make opt-in changes explicit.
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Can adding a field break an AI agent?
Yes, depending on where it is added and how the agent uses schemas. An optional response field that an agent ignores is usually safe. A newly required request field, a field whose description changes the recommended action, or an output field that causes a cached tool schema to be refreshed incorrectly can break the workflow. Additive changes are safest when they are optional, have an unambiguous description, preserve defaults, and are tested against older schemas and prompts.
Choose how consumers select a version
There is no universal winner between URL paths, headers and query parameters. Pick one mechanism, document its scope, and make the selected version visible in examples, generated client configuration, request logs and support diagnostics.
| Mechanism | Advantages | Costs and agent considerations |
|---|---|---|
Major version in URL path, such as /v2/ |
Highly visible in copied URLs, logs and gateway routing; easy for a consumer to pin. | Creates distinct resource URLs and can require routing or documentation for each major version. Google’s traditional REST guidance uses this approach for incompatible major changes. |
| Version in an HTTP header | Keeps resource URLs stable and supports date-based or interface-specific versions. GitHub selects REST versions with the X-GitHub-Api-Version header. |
Clients, proxies and logs must preserve and display the header. An omitted header needs a clearly documented fallback; otherwise behavior can change silently when an old version leaves support. |
| Version in a query parameter | Easy to inspect during manual testing and can support interface-level selection. | Parameters can leak into copied URLs, cache keys and analytics. Every cache and signature layer must include the version when it affects the response. |
| Interface or element-level version | Lets independent surfaces evolve without forcing a whole-service migration. Google AIP-185 describes version identifiers carried in a header or query parameter. | Requires stronger annotations, tooling and documentation so an agent knows which interface versions compose safely. |
For repeatable agent behavior, pin a concrete version in production. Use negotiation only when both sides implement an explicit fallback rule: the client advertises supported versions or capabilities, the server selects one, and the selected contract is recorded in telemetry. Never silently reinterpret an unversioned request as a new contract.
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Keep names and meanings durable
Choose operation and tool names that describe an enduring capability rather than an implementation detail. If a tool creates an invoice, keep that meaning stable even if the backend changes. When a behavior truly must change, expose a new operation or version-specific tool rather than reusing the old name with a subtly different result. Keep human-readable descriptions synchronized with machine-readable schemas; an agent relies on both.
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Make defaults explicit
Document every default that can affect an agent’s decision: page size, sort order, filtering, time zone, idempotency behavior, retry policy and safety mode. Preserve the old default in an existing version. If a new default is desirable, introduce it in a new version or behind an opt-in parameter whose absence retains the old behavior. Include the effective default in responses or diagnostics when ambiguity would be dangerous.
Use open-world parsing for extensible values
Agents and wrappers should tolerate unknown response fields and enum values when the protocol permits it. Producers should state whether an enum is closed or may grow. For actions with safety implications, an unknown value should fail safely and produce a useful error rather than being interpreted as a permissive fallback.
Stabilize errors and capabilities
Keep error categories, retryability and required remediation consistent within a version. A changed status code or error field can make an agent retry a non-retryable operation or abandon a recoverable one. Publish capability discovery separately from transient operational state, and version the discovery response when its shape or meaning changes.
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Account for schema discovery and caching
Agent wrappers and SDKs may list tools, download their input and output schemas, and cache those definitions. The Agents SDK documentation describes MCP tool listing and optional tool-list caching when definitions do not change frequently. It does not define a universal cache lifetime, so your service must specify freshness behavior.
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- Give each schema a version or revision identifier and expose it in discovery responses.
- Document cache-control, refresh triggers and a manual refresh operation or configuration switch.
- Keep old tool definitions available while clients refresh; do not invalidate a cached name without a migration path.
- Record the discovered schema revision and selected API version with each tool call so failures can be reproduced.
- When an input or output shape changes incompatibly, publish a version-specific tool surface or a new stable name.
An agent that cached yesterday’s definition may continue sending yesterday’s arguments after the server deploys today’s schema. Plan for that interval deliberately instead of treating discovery as an instantaneous event.
Separate stable releases from previews
Do not promise production compatibility for a preview feature. Google Compute Engine distinguishes stable versions, which retain strict compatibility expectations, from preview versions whose features may change or be removed. Label preview operations and schemas prominently, give them an owner and an expected review date, and require an explicit opt-in. Recommend stable client libraries for production workloads. A preview can graduate into a stable contract, but graduation should not silently alter an existing stable operation.
An Internet-Draft about HTTP APIs consumed by AI agents and tool-calling layers, including MCP, is emerging guidance rather than a finalized IETF standard. You may use it to inform design discussions, but your compatibility promises should rest on a published version policy and tested behavior.
Plan a coexistence and migration window
Launch a successor before withdrawing the old contract. A practical sequence is:
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- Announce the change. Name the successor version, affected operations, changed defaults, validation rules and planned dates. State whether the change is breaking, additive or preview-only.
- Publish schemas and examples. Provide machine-readable definitions, before-and-after requests and responses, error mappings, authentication changes and representative agent instructions.
- Run both contracts. Route old and new versions independently, and keep their operation semantics isolated. If a single backend serves both, maintain version-specific translation at the boundary.
- Instrument usage. Measure calls by version, operation, client identity and schema revision. Contact owners of active old clients rather than relying only on a general announcement.
- Signal deprecation. Where appropriate, return
DeprecationandSunsetresponse headers and include the dates in documentation and dashboards. - Verify migration. Ask consumers to run contract tests and switch their pinned version. Test retries, pagination, authorization failures, unknown enum values and stale discovery caches.
- Retire deliberately. After the announced window, reject the old version with a documented error that identifies the replacement. Preserve migration documentation and a support path for archived clients.
How long should an old version stay supported?
Set the window according to client update cycles, risk and the cost of operating two contracts, then publish it before launch. GitHub’s current REST documentation is a concrete policy example: it supports the previous version for at least 24 months after a newer version is released and documents deprecation and sunset headers. That is GitHub’s policy, not a universal requirement. Google AIP-185 calls for a reasonable, well-communicated deprecation period and recommends 180 days for shutting down beta releases in its release model. Do not copy either number without considering your own consumers.
State exceptions in the policy. GitHub notes that critical security, data-exposure or severe reliability issues can require an unscheduled version or, rarely, a breaking change outside the ordinary cadence. A compatibility promise should explain this emergency path instead of implying that no exception is possible.
Test every supported contract
Build contract checks around the compatibility dimensions rather than relying on a single schema diff.
- Schema checks: detect removed or renamed fields, type changes, newly required inputs, enum removal and incompatible constraints.
- Wire checks: send representative requests from each supported version and verify decoding, status codes, content types and error envelopes.
- Semantic checks: assert defaults, pagination completeness, ordering, units, authorization outcomes and retryability.
- Agent checks: run representative older tool schemas and prompts through the new server; confirm that the selected operation, arguments and safety checks remain correct.
- Discovery checks: test fresh and stale schema caches, revision changes, refresh instructions and coexistence of old and new tool names.
- Operational checks: verify version headers or paths survive gateways, signing, caching, tracing and log aggregation.
Keep a fixture for every released schema and a small set of real-world client configurations. A generated client can pass a wire test while an agent still fails semantically, so include assertions about the action chosen and the meaning inferred from the response.
Migration guidance consumers can follow
- Identify the version actually sent in production, including implicit defaults and cached tool-schema revisions.
- Read the breaking-change list and compare old and new schemas field by field.
- Pin the successor version explicitly in the client or request header; do not depend on an unversioned default.
- Update tool descriptions, examples, enum handling, pagination loops and error-retry logic together.
- Refresh discovery caches and record the new schema revision.
- Run contract and agent behavior tests against a staging endpoint, including authorization failures and partial results.
- Deploy with telemetry that can separate old and new versions, then watch for unexpected operation selection or validation errors.
Migration notes should show concrete before-and-after payloads, not only a list of renamed fields. Explain why a model might choose a different tool, how to preserve an old result set, and what response indicates that the client selected an unsupported version.
A policy template for API owners
A concise policy can answer the questions consumers ask before they integrate:
- What counts as a breaking, additive or preview change?
- Where is the version selected, and what happens when it is omitted?
- Which contract elements are stable: names, schemas, defaults, errors, authorization and semantics?
- How are tool schemas discovered, cached, invalidated and revised?
- How long are released and beta versions supported, and when are deprecation and sunset signals sent?
- How are emergency security or reliability exceptions handled?
- Where are migration schemas, changelogs, test fixtures and contact details published?
Stripe’s Brandur Leach described an API as a communication contract that cannot be changed without considerable cooperation and effort in a 2017 API-versioning article. That observation applies even more strongly when a model, rather than a hand-maintained client, turns the contract into actions. Treat every published schema and description as production interface surface, make incompatible behavior selectable, and give agents enough time and telemetry to move.
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