The agent asked for confirmation because the system prompt told it to, and read
the answer itself. Both halves are now enforced.
Each MCP toolset is wrapped in ApprovalRequiredToolset whose predicate reads the
readOnlyHint the server publishes — the gateway decides what counts as a write,
and the agent keeps no list of tool names in step with it.
output_type=[str, DeferredToolRequests] lets a turn end holding a proposed call
instead of making it; the executor parks the A2A task in input-required and
renders the arguments the model actually sent, not what it said it would do.
The reply is matched against a closed set of words, so "oui mais change le prix"
denies the call and the correction comes back for approval on its own merits —
verified end to end, along with a draft the user approved that was still refused
because msrp sat below buyprice.
Also wired: a ProductDraft validated after approval and before the call leaves;
UsageLimits on every run; FilteredToolset denying sales' write tools inside the
agent as well as at the gateway; PrefixedToolset namespacing the two servers;
dynamic instructions naming the caller; Agent.instrument_all() for a span per
model call and per tool call; and pydantic_ai.retries on inference only, so a
429 from the gateway is waited out rather than failing mid-reasoning.
Inference gets its own httpx client: validate_response raises on any 4xx, and
applying that to the shared client would turn a token-exchange refusal into an
exception carrying no body — which is where Keycloak says what was wrong. Its
transport is built explicitly, because a transport passed to the client makes
verify= inert and the lab CA would otherwise go undeclared.
Tests grew from 7 to 31, covering what approval decides and what a draft must
satisfy. evals/catalogue_evals.py adds a behavioural suite, kept out of pytest
because every case spends real tokens; its first case checks that a count comes
from the tool rather than from what the model remembers of a public dataset.
CLAUDE.md corrected: instrument=True is not an Agent parameter in 2.35.3,
pydantic_ai.retries needs tenacity, TemplateStr needs pydantic-handlebars, and
approval does not remove the in-memory history — resuming still needs the
messages, so replicas: 1 stands until they live in the A2A task store.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
The broker client was renamed in Keycloak so that the contract an agent has to
honour no longer names the middleware serving it. This is the last consumer to
move; the gateways and LibreChat went first.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
An agent talks to URLs that honour a contract: an MCP endpoint, an OIDC token
endpoint, an OpenAI-shaped LLM endpoint. Whatever serves those URLs is
replaceable, and naming it in an agent's code or docs implies a coupling that
does not exist.
Every product name is gone from prose, comments and identifiers, replaced by
what the agent actually depends on. Where a behaviour of the current middleware
leaks into the contract — the second audience scope, the tool ACL — the text
now says what the caller must do and why, not who imposes it.
One string survives and cannot be fixed here: the broker client an agent must
name in its audience scopes is itself named after the middleware. Closing that
means renaming it in Keycloak and following the rename through the gateway
configuration and LibreChat. Recorded as a blocker.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Two things, both discovered by instrumenting the failure rather than trusting
the message it printed.
The MCP session never failed on protocol. macOS resolves any `.local` name
through mDNS first and takes a flat ~5.0s doing it, which sits exactly on
httpx's 5s default connect timeout; fastmcp reported the resulting
ConnectTimeout only as "Failed to initialize server session". Earlier tests
used `curl --resolve`, which bypasses DNS entirely and made it look like DNS
had been eliminated. Settings.http_timeout (60s) now covers the shared client,
the client fastmcp builds, and MCPToolset's init_timeout. list-products,
get-product and create-product now enumerate over the real gateway.
Inference used a static "unused" api_key against a gateway whose
openid-connect plugin requires audience ["llm-proxy"]. The model call now
carries a token exchanged for llm-proxy-audience, so it is attributable to the
same (agent, end user) pair as every tool call.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Design agreed in discussion, nothing built yet. Records the agent's role, its
scopes and MCP servers, its A2A surface, and the framework choice with its
reason — so the next session starts from the decisions rather than re-deriving
them.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Stéphane Tailland