Test Endpoint · Microsoft Foundry · microsoft/azure-skills · Skills Docs

Test Endpoint · Microsoft Foundry · microsoft/azure-skills · Skills Docs

TOKEN=$(az account get-access-token --resource https://ai.azure.com --query accessToken -o tsv)
TOOLBOX_URL="https://<account>.services.ai.azure.com/api/projects/<project>/toolboxes/<name>/mcp?api-version=v1"

curl -sS -X POST "$TOOLBOX_URL" \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2025-03-26","capabilities":{},"clientInfo":{"name":"debug","version":"1.0.0"}}}' \
  -D - | head -20

curl -sS -X POST "$TOOLBOX_URL" \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"jsonrpc":"2.0","id":2,"method":"tools/list","params":{}}' | python -m json.tool

# web_search — arg is `search_query` (returns live Bing results)
curl -sS -X POST "$TOOLBOX_URL" -H "Authorization: Bearer $TOKEN" -H "Content-Type: application/json" \
  -d '{"jsonrpc":"2.0","id":3,"method":"tools/call","params":{"name":"<web_search_tool_name>","arguments":{"search_query":"latest Azure Foundry news"}}}' | python -m json.tool

# code_interpreter — arg is `code` (spins up a sandbox container and runs it; isError=false)
curl -sS -X POST "$TOOLBOX_URL" -H "Authorization: Bearer $TOKEN" -H "Content-Type: application/json" \
  -d '{"jsonrpc":"2.0","id":4,"method":"tools/call","params":{"name":"<code_interpreter_tool_name>","arguments":{"code":"print(6*7)"}}}' | python -m json.tool

# 1. Read the endpoint and set the env var
azd env set TOOLBOX_ENDPOINT "$(azd ai toolbox show <toolbox-name> --output json | python -c "import sys,json; print(json.load(sys.stdin)['endpoint'])")"

# 2. Reference TOOLBOX_ENDPOINT in the agent service's environmentVariables in azure.yaml, then deploy
azd deploy

# 3. Invoke the agent to confirm it sees and can call the tool
azd ai agent invoke "list the tools you have access to"

{"jsonrpc":"2.0","id":2,"error":{"code":-32006,
 "message":"tools/list failed for 1 tool source(s)... {\"errors\":[{\"name\":\"<server_label>\",\"type\":\"mcp\",
   \"error\":{\"code\":\"CONSENT_REQUIRED\",
     \"message\":\"https://logic-apis-<region>.consent.azure-apim.net/login?data=...\"}}]}"}}

Symptom	Likely cause / fix
`tools/list` → `-32006 CONSENT_REQUIRED`	Expected on first use. Open the returned consent URL and sign in; retry.
`tools/list` → `-32007 HTTP_403` after consenting	Consent succeeded, but the MCP server rejected the token — its Easy Auth doesn’t advertise the scope. For a self-built Functions MCP, set `WEBSITE_AUTH_PRM_DEFAULT_WITH_SCOPES=<ENTRA_IDENTIFIER_URI>/user_impersonation` on the Function App (see tool-mcp-custom-oauth-azure-starter.md).
`tools/list` → `-32007 HTTP_404`	Auth passed but the server has no tools at `/runtime/webhooks/mcp` — the MCP code isn’t deployed. Publish a sample with `func azure functionapp publish <app>`.
`AADSTS...redirect_uri` mismatch after clicking consent	The connection’s reply URL isn’t registered on your app. Read `properties.redirectUrl` from the connection and add it to the app’s redirect URIs — see tool-mcp-custom-oauth.md § Set the connector redirect URI.
`invalid_client` at the token step	Wrong `--client-secret` (expired/mistyped) or `--client-id`. Reset the secret and recreate the connection.
`tools/list` returns zero after consent	Scope mismatch — `--scopes` must match the MCP’s `scopes_supported` from `/.well-known/oauth-protected-resource`.
`tools/call` → `403 ... user may not be registered`	Managed connector backed by a dogfood OAuth app with a test-user allowlist — not fixable client-side. See foundry-tool-catalog.md dogfood trap.