diff --git a/inference-platforms/README.md b/inference-platforms/README.md
index af38c60..18ecc7e 100644
--- a/inference-platforms/README.md
+++ b/inference-platforms/README.md
@@ -19,6 +19,43 @@ Elastic Stack.
 * [AgC](AgC) - with [OpenTelemetry export][AgC]
 * [vLLM](vllm) - with [OpenTelemetry POC][vllm] configuration
 
+## MCP Agent flow
+
+[agent.py](agent.py) uses the [OpenAI Agents SDK][openai-agents] to search for
+flights via [Kiwi's MCP server][kiwi-mcp], proxied through an inference
+platform like [Envoy AI Gateway](aigw).
+
+```mermaid
+sequenceDiagram
+    participant Agent
+    participant Gateway as AI Gateway
+    participant LLM as LLM Server
+    participant MCP as MCP Server
+
+    Agent ->> Gateway: user: "Use the search-flight tool to search for flights from New York to Los Angeles on 18/03/2026"
+    Gateway ->> LLM: ChatCompletion
+    activate LLM
+    LLM ->> Gateway: tool_call: search-flight({origin: "JFK", destination: "LAX", departureDate: "18/03/2026"})
+    deactivate LLM
+    Gateway ->> Agent:
+    activate Agent
+
+    Agent ->> Gateway: tools/call: search-flight
+    Gateway ->> MCP: tools/call: search-flight
+    activate MCP
+    MCP -->> Gateway: {flights: [{price: 177, route: "JFK→ATL→LAX"}, ...]}
+    deactivate MCP
+    Gateway -->> Agent:
+    deactivate Agent
+
+    Agent ->> Gateway: [user, assistant, tool: {flights}]
+    Gateway ->> LLM: ChatCompletion
+    activate LLM
+    LLM ->> Gateway: "The cheapest flight is JFK → ATL → LAX for €177..."
+    deactivate LLM
+    Gateway ->> Agent:
+```
+
 If you use Elastic Stack, an example would look like this in Kibana:
 
 ![Kibana screenshot](./kibana-trace.jpg)
@@ -114,3 +151,5 @@ To start and use Ollama, do the following:
 [uv]: https://docs.astral.sh/uv/getting-started/installation/
 [ollama-dl]: https://ollama.com/download
 [otel-tui]: https://github.com/ymtdzzz/otel-tui
+[openai-agents]: https://github.com/openai/openai-agents-python
+[kiwi-mcp]: https://mcp.kiwi.com
diff --git a/inference-platforms/agent.py b/inference-platforms/agent.py
index f5032a1..91f1f4e 100644
--- a/inference-platforms/agent.py
+++ b/inference-platforms/agent.py
@@ -41,10 +41,11 @@ async def run_agent(tools: list[Tool], model_name: str, use_responses: bool):
         tools=tools,
     )
 
-    next_week = (datetime.now() + timedelta(weeks=1)).strftime("%Y-%m-%d")
+    # Small models can't convert between date formats that may be required by tools so this format needs to be precise
+    next_week = (datetime.now() + timedelta(weeks=1)).strftime("%d/%m/%Y")
     result = await Runner.run(
         starting_agent=agent,
-        input=f"Give me the best flight from New York to Kota Kinabalu on {next_week}",
+        input=f"Use the search-flight tool to search for flights from New York to Los Angeles on {next_week}",
         run_config=RunConfig(workflow_name="flight search"),
     )
     print(result.final_output)
diff --git a/inference-platforms/aigw/README.md b/inference-platforms/aigw/README.md
index 4f29685..43cb008 100644
--- a/inference-platforms/aigw/README.md
+++ b/inference-platforms/aigw/README.md
@@ -30,6 +30,8 @@ Start Ollama and your OpenTelemetry Collector via this repository's [README](../
 
 ## Run Envoy AI Gateway
 
+### Run with Docker
+
 ```bash
 docker compose up --force-recreate --pull always --remove-orphans --wait -d
 ```
@@ -40,6 +42,20 @@ Clean up when finished, like this:
 docker compose down
 ```
 
+### Run with Go
+
+Download [shdotenv](https://github.com/ko1nksm/shdotenv) to load `env.local` when running.
+
+```
+curl -O -L https://github.com/ko1nksm/shdotenv/releases/download/v0.14.0/shdotenv
+chmod +x ./shdotenv
+```
+
+Run `aigw` from source after setting ENV variables like this:
+```bash
+./shdotenv -e env.local go run github.com/envoyproxy/ai-gateway/cmd/aigw@latest run --mcp-json '{"mcpServers":{"kiwi":{"type":"http","url":"https://mcp.kiwi.com"}}}'
+```
+
 ## Call Envoy AI Gateway with python
 
 Once Envoy AI Gateway is running, use [uv][uv] to make an OpenAI request via
@@ -51,6 +67,11 @@ Once Envoy AI Gateway is running, use [uv][uv] to make an OpenAI request via
 OPENAI_BASE_URL=http://localhost:1975/v1 uv run --exact -q --env-file env.local ../chat.py
 ```
 
+Or, for the OpenAI Responses API
+```bash
+OPENAI_BASE_URL=http://localhost:1975/v1 uv run --exact -q --env-file env.local ../chat.py --use-responses-api
+```
+
 ### MCP Agent
 
 ```bash
@@ -60,10 +81,9 @@ OPENAI_BASE_URL=http://localhost:1975/v1 MCP_URL=http://localhost:1975/mcp uv ru
 ## Notes
 
 Here are some constraints about the Envoy AI Gateway implementation:
-* Until [this][openai-responses] resolves, don't use `--use-responses-api`.
+* Access log integration currently requires the OTLP gRPC transport (`OTEL_EXPORTER_OTLP_PROTOCOL=grpc`).
 
 ---
 [docs]: https://aigateway.envoyproxy.io/docs/cli/
 [openinference]: https://github.com/Arize-ai/openinference/tree/main/spec
 [uv]: https://docs.astral.sh/uv/getting-started/installation/
-[openai-responses]: https://github.com/envoyproxy/ai-gateway/issues/980
diff --git a/inference-platforms/aigw/docker-compose.yml b/inference-platforms/aigw/docker-compose.yml
index eb597d6..8ff9b7a 100644
--- a/inference-platforms/aigw/docker-compose.yml
+++ b/inference-platforms/aigw/docker-compose.yml
@@ -36,7 +36,7 @@ services:
     environment:
       - OTEL_SERVICE_NAME=aigw
       - OPENAI_BASE_URL=http://host.docker.internal:11434/v1
-      - OTEL_EXPORTER_OTLP_ENDPOINT=http://host.docker.internal:4318
+      - OTEL_EXPORTER_OTLP_ENDPOINT=http://host.docker.internal:4317
     ports:
       - "1975:1975" # OpenAI compatible endpoint at /v1, MCP server at /mcp
     configs:
diff --git a/inference-platforms/aigw/env.local b/inference-platforms/aigw/env.local
index 6cf23b7..ad65c9a 100644
--- a/inference-platforms/aigw/env.local
+++ b/inference-platforms/aigw/env.local
@@ -10,10 +10,8 @@ MCP_HEADERS=
 
 # OpenTelemetry configuration
 OTEL_SERVICE_NAME=openai-agent
-OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4318
-OTEL_EXPORTER_OTLP_PROTOCOL=http/protobuf
-OTEL_TRACES_EXPORTER=otlp
-OTEL_METRICS_EXPORTER=otlp
+OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4317
+OTEL_EXPORTER_OTLP_PROTOCOL=grpc
 
 # Reduce trace and metrics export delay for demo purposes
 OTEL_BSP_SCHEDULE_DELAY=100
diff --git a/inference-platforms/chat.py b/inference-platforms/chat.py
index 9d290e3..69c7aec 100644
--- a/inference-platforms/chat.py
+++ b/inference-platforms/chat.py
@@ -45,7 +45,7 @@ def main():
         response = client.responses.create(
             model=model, input=messages[0]["content"], temperature=0, extra_body=extra_body
         )
-        print(response.output[0].content[0].text)
+        print(response.output_text)
     else:
         chat_completion = client.chat.completions.create(
             model=model, messages=messages, temperature=0, extra_body=extra_body
diff --git a/inference-platforms/kibana-trace.jpg b/inference-platforms/kibana-trace.jpg
index 7bd1dac..c00d06e 100644
Binary files a/inference-platforms/kibana-trace.jpg and b/inference-platforms/kibana-trace.jpg differ