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Last week was Fable 5 billing, GitHub Models’ first brownout, and WAIC. This week is about migrations: three separate systems change their behavior on three separate days, open weights land on a fourth, and the MCP specification that has been in release-candidate for ten weeks becomes final on a fifth. If you have any of the affected integrations, the deadlines are not clustered — they each require a separate audit.

Here is the full calendar.

Anthropic Agent-Memory API Breaking Changes: July 22

What it is: On July 22, the agent-memory-2026-07-22 beta header changes how the GET /v1/memory_stores/{memory_store_id}/memories endpoint behaves. These are not additive changes — they alter response shape and validation in ways that will break existing code silently or loudly depending on how you use the API.

Three specific changes:

Parameter Old behavior New behavior after July 22
order_by, order Accepted and applied Ignored; results returned in stable, server-defined order
depth Any integer accepted Only 0 (whole subtree), 1 (immediate children), or omitted; other values return HTTP 400
path_prefix Substring match Must end with /; matches whole path segments only — path_prefix=/notes/ returns /notes/todo.md but not /notes-archive/todo.md

The pagination trap: If you switch from managed-agents-2026-04-01 to agent-memory-2026-07-22 mid-session, page cursors from the old header are not valid with the new one. You must restart from page one. Code that tries to resume pagination across a header change will receive an error or a duplicate result set.

What to audit now: Search your codebase for any call to GET /v1/memory_stores/*/memories and check: (1) whether you pass order_by or order and depend on that ordering downstream; (2) whether you pass depth with a value other than 0 or 1; (3) whether you use path_prefix with a value that doesn’t end in / or that relies on substring matching.

For the full migration diff and test cases, see our agent-memory breaking changes guide.

GitHub Models Second Brownout: July 23

What it is: GitHub will run a second simulated outage for GitHub Models on Thursday. Requests return errors for a short window before service is restored. The final, permanent shutdown is July 30 — no brownout, no recovery.

Why the second brownout matters: The July 16 first brownout was designed to surface hidden dependencies. This second one is the verification pass — if you patched integrations after July 16, Thursday tells you whether the patch worked. If you didn’t patch, Thursday gives you one more week to find what’s still broken before the hard shutdown.

Builder action: If your July 16 brownout produced zero incidents, you are likely clear. If it produced incidents and you patched, let Thursday’s brownout confirm. If you haven’t migrated at all — Azure AI Foundry is the recommended production destination; OpenRouter and direct provider APIs are the self-managed alternative.

The July 30 shutdown is not negotiable: There are no brownout windows after July 23. Full shutdown on July 30 means requests fail permanently. Do not leave GitHub Models in any production path.

For the full migration map and Foundry setup, see our GitHub Models retirement guide.

DeepSeek V4 Migration Deadline: July 24

What it is: DeepSeek’s API stops resolving the legacy model name deepseek-v4 on July 24. Calls that use the old string will fail after this date.

Why this matters more than a typical deprecation: DeepSeek V4 was a significant release — pricing at roughly $0.44 per million output tokens, approximately 75% below current frontier competitors — and got wide adoption across builders routing price-sensitive workloads. If you adopted it during the pricing arbitrage window and haven’t touched that integration since, the model name in your config or environment variable is almost certainly the legacy string.

The specific change: The legacy string deepseek-v4 no longer resolves. The current model identifiers for V4-class inference are documented in DeepSeek’s API reference. The thinking-mode variant and the flash variant have separate model strings — pick the one that matches your actual use.

What to audit: Search for deepseek-v4 as a literal string in config files, environment variables, .env files, and any database rows where you store model identifiers. Do not assume your SDK will handle the alias — it won’t.

For the migration decision tree and thinking-mode trap, see our DeepSeek V4 migration guide and the July 24 deadline update.

Kimi K3 Open Weights: July 27

What it is: Moonshot AI has committed to releasing Kimi K3’s full weights on Hugging Face by July 27, alongside a technical report with architecture and training details. As of today, the weights are not yet public — this is a commitment, not an accomplished fact.

Why the weights matter: Kimi K3 is 2.8 trillion total parameters with 50 billion active per forward pass (MoE architecture). It is the largest open-weight model announced to date — VentureBeat and Axios both covered the release as a frontier-tier event. On Arena.ai’s Frontend Code Arena, it holds the #1 position with a 76% pairwise win rate — reported by AI News Daily on July 18. The open weights release ships under Modified MIT license — no royalties on fine-tuned derivatives.

Hardware reality: Full weights in MXFP4 quantization require approximately 1.4 TB of weight storage. This is not a consumer workload. Self-hosting K3 requires Blackwell-class infrastructure or a multi-node A100/H100 cluster. If you don’t have that, the practical on-ramp is the Kimi API (currently $3/MTok input, $15/MTok output) or one of the managed inference providers that will pick up the weights after release.

The technical report: Architecture and training details ship with the weights. Given the scale, the report will likely clarify how Stable LatentMoE differs from standard MoE implementations and how MXFP4 quantization-aware training preserves benchmark fidelity at compressed precision.

Watch for: Moonshot’s Hugging Face organization. The exact file naming and shard structure will determine which inference stacks can serve it day one.

For K3 API details and what’s live now, see our Kimi K3 builder guide.

MCP 2026 Specification Final Ratification: July 28

What it is: The Model Context Protocol’s 2026-07-28 release candidate, locked on May 21, becomes the final specification on July 28. This closes the ten-week validation window and makes the specification binding for SDK maintainers and production server operators.

What changed from the current spec: The 2026-07-28 spec is the largest revision since MCP’s initial release. Six headline changes:

  1. Sessions removed: The spec’s core is now stateless — session handshake and session IDs are gone. Servers can run behind ordinary round-robin load balancers without sticky sessions.
  2. Two new required HTTP headers: All MCP HTTP transports must send these headers; their absence causes the SDK to reject the connection. Existing servers that don’t add them before July 28 will break with compliant clients.
  3. Error codes changed: The numeric error code set was reorganized. Code that branches on specific error numbers needs to be updated.
  4. MCP Apps: Servers can now serve interactive HTML UIs in sandboxed iframes — a new capability class that didn’t exist in the prior spec.
  5. Tasks extension: Formal protocol support for long-running work items with status polling. Previously this was handled ad-hoc; it’s now a first-class primitive.
  6. Roots/Sampling/Logging deprecated: These three features were deprecated in the RC. They still work in July 28 but are formally on the path to removal.

The OAuth/OIDC alignment: The authorization model was brought into conformance with OAuth 2.0 and OIDC. Servers using the prior authorization approach need to update their token validation logic.

SDK status: SDK maintainers have had the full ten weeks since May 21 to ship support. Most major SDKs (TypeScript, Python) have already shipped compliant versions in their release candidates. Check your MCP SDK version before July 28 — if you’re on a pre-RC release, the final spec will add new protocol behavior your SDK doesn’t handle.

For the full breaking change list and migration checklist, see our MCP 2026 RC guide.

GitHub Models Full Shutdown: July 30

What it is: GitHub Models permanently shuts down on July 30, 2026. All requests to the GitHub Models API return errors from this point forward with no restoration.

Why this is categorically different from a brownout: The July 16 and July 23 brownouts are short windows that return to service. July 30 is permanent. There is no “wait for recovery” option.

If you are still on GitHub Models on July 29: You have one day. The recommended migration path is Azure AI Foundry for production workloads. OpenRouter or direct provider APIs are the self-managed alternative. The model catalog on GitHub Models overlaps substantially with what’s available on Foundry — most model names translate directly.

For the migration guide, see our GitHub Models retirement guide.

What Is NOT This Week, But Close

Coming after this week:

  • Kimi K3 open weights are promised by July 27 — but the technical report shipping with them may clarify questions about fine-tuning behavior and quantization fidelity that will drive adoption decisions in early August.
  • MCP DevDays (July 29–30): Microsoft is hosting two days of MCP developer sessions back-to-back with the spec’s ratification date. Expect integration demos, first-party SDK updates, and the first production examples built against the 2026-07-28 spec.
  • Gemini 3.5 Pro: No confirmed date. The third slip past July 17 makes a July/early-August window plausible, but Google has not published a model card, pricing, or API endpoint.
  • DeepSeek V4 stable release: Expected July 24 — the same day the old model name dies. The stable release is distinct from the migration deadline; watch for updated benchmarks and fine-tuning documentation.

The Week at a Glance

When What Action
July 22 (Wed) Anthropic agent-memory-2026-07-22 breaking changes Audit list-memories calls for depth, path_prefix, and order_by usage
July 23 (Thu) GitHub Models second brownout Verify July 16 patches; identify any remaining hidden dependencies
July 24 (Fri) DeepSeek V4 model name deepseek-v4 stops resolving Update model strings in config, env vars, and any stored identifiers
July 27 (Sun) Kimi K3 open weights on Hugging Face Watch Moonshot’s HF org; plan hardware or provider evaluation
July 28 (Mon) MCP 2026 specification goes final Confirm SDK version compliance; verify new headers and stateless transport
July 30 (Wed) GitHub Models permanent shutdown Complete migration before this date — no recovery option after

Three migrations, one open weights release, one protocol ratification, and a permanent API shutdown — all in eight days. The agent-memory change is the most likely to be overlooked because it affects only builders on the managed agents beta; the GitHub Models shutdown is the most consequential if missed.