Stéphane Tailland 0bc06512f5 fix: unblock the MCP session, and authenticate to the AI gateway with OIDC
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>
2026-08-28 11:01:18 +02:00

Catalogue

Product management agent for the Classic Models catalog domain. Serves a product manager: what exists, how it is priced, whether it sells, what to discontinue.

Reached over A2A; reads data over MCP through the Kong gateways; thinks through the Kong AI gateway. It is one MCP client among others, exactly as LibreChat is — nothing under it changes to accommodate it.

Running it

uv venv && uv pip install -e ".[dev]"
export CATALOGUE_CLIENT_SECRET=...        # Keycloak client secret, no default
export CATALOGUE_CA_BUNDLE=/path/to/sttlab-local-ca.crt
python -m catalogue_agent

Everything else has a working default in config.py and is overridable with CATALOGUE_-prefixed variables.

curl localhost:8080/.well-known/agent-card.json

curl -X POST localhost:8080/ \
  -H 'Content-Type: application/json' \
  -H 'A2A-Version: 1.0' \
  -H "Authorization: Bearer $USER_TOKEN" \
  -d '{"jsonrpc":"2.0","id":1,"method":"SendMessage",
       "params":{"message":{"messageId":"m1","role":"ROLE_USER",
                            "parts":[{"text":"How many product lines are there?"}]}}}'

A2A-Version: 1.0 is required. Without it the SDK assumes 0.3 and answers VERSION_NOT_SUPPORTED, which reads as a protocol error even though the request is fine.

How a turn works

A2A SendMessage  ──►  exchange the user's token, once per audience
                 ──►  build one MCP toolset per server, with that turn's tokens
                 ──►  PydanticAI runs the model through the Kong AI gateway
                 ──►  answer, toolsets dropped

The MCP client is built per turn. A token that outlives the turn it was minted for is a token that can be replayed after the user's session ended, and holding one long-lived connection would mean one long-lived token.

Several narrow tokens rather than one broad one: a token minted for mcp-catalog is refused by the sales gateway, so a prompt injection that talks the agent into reaching the wrong domain fails at Kong rather than succeeding quietly.

What it can and cannot do

Reads catalog (products, product lines), sales (read-only, to judge whether a product sells)
Writes none yet — the agent says so when asked
Calls nothing yet. Approvisionnement.check_availability comes with discontinuation decisions
Exposes describe_catalog

Skills are decision-shaped on purpose. An agent exposing a generic query has become a data proxy and defeats the per-domain scoping the estate is built on, so skills get added when another agent has a specific question — not in advance.

Two Keycloak facts this depends on

Both measured against Keycloak 26.6, both costly to rediscover:

actor_token is silently ignored. Standard Token Exchange accepts it, returns a valid token and emits no act claim — no error. Delegation cannot be built on RFC 8693 act; the actor is identified by azp, which carries this agent's client id while sub stays the human.

The audience is requested as a scope. audience=mcp-catalog returns "Requested audience not available". scope=openid mcp-catalog-audience works.

Library choices

Pinned to what was current on 2026-08-28, ranges below the next major so patch fixes arrive but an upgrade stays deliberate.

a2a-sdk rather than FastA2A. The earlier design said FastA2A, on the grounds that Agent.to_a2a() was going away in PydanticAI v2 — which has since happened, so that argument no longer distinguishes them. This estate exists to prove A2A interoperability across five runtimes, and the reference implementation is the safer thing for four other stacks to interoperate with.

httpx2 rather than httpx. PydanticAI deprecates httpx clients for OpenAI-compatible providers and removes them in v3.

Notes on a2a-sdk 1.1 that are not guessable, all established against the running library:

  • a2a.types are protobuf messages, not pydantic models.
  • Use DefaultRequestHandlerV2; DefaultRequestHandler speaks 0.3.
  • JSON-RPC methods are SendMessage, GetTask… The 0.3 spelling (message/send) still works — enable_v0_3_compat is on.
  • An executor must enqueue a Task before any status update when context.current_task is None.

Not done yet

  • The Keycloak client does not exist. classic-models-agent-catalogue has to be declared in infra-keycloak/k8s/keycloak/configmap-realm.yaml, with mcp-catalog-audience and mcp-sales-audience as optional scopes. Until then the exchange fails and the agent says so.
  • Writes, and the A2A call to Approvisionnement.
  • Deployment manifests — they belong in classic-models-agent-platform once a second agent shows what is actually shared.
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