We recently added outputSchema support for our MCP tools (not yet for
worker routes yet). Today, we always return structuredContent. On tool
execution errors we return structuredContent: {"error": "..."} with
isError: True, even when that shape does not match the tool’s declared
outputSchema. Since the MCP spec says clients SHOULD validate
structuredContent against outputSchema, some clients reject these
responses.
Since structuredContent is optional, we’re going to omit it when
isError: true.
<!-- CURSOR_SUMMARY -->
---
> [!NOTE]
> **Medium Risk**
> Changes the shape of tool error responses across the MCP server, which
may break clients or tools that previously relied on
`structuredContent["error"]` for failures. Behavior is more
spec-compliant but touches core request/response paths and test
expectations.
>
> **Overview**
> Prevents MCP tool error responses from violating a tool’s declared
`outputSchema` by **always setting `structuredContent=None` when
`isError=True`** (server execution errors, unknown tools, middleware
exceptions, and `Context.tools.call_raw` JSON-RPC errors).
>
> Updates requirement-failure error formatting to put the human-friendly
message in `content[0]` and (when present) serialize extra
machine-readable fields (e.g. `authorization_url`, `llm_instructions`)
into an additional `content` item. Examples and integration/unit tests
are updated to read errors from `content[0].text`, and
`arcade-mcp-server` is bumped to `1.19.2`.
>
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When a tool’s output TypedDict uses total=False, MCP clients reject the
response with:
```
MCP error -32602: Structured content does not match the tool's output schema
```
Note that the bug also exists for the Engine transport
(/worker/tools/execute), but since the engine doesn't validate the
output schema, the bug never surfaced. This PR addresses the problem
holistically (MCP and Engine) in preparation for a future where the
Engine transport validates output schemas.
Two bugs combined to cause this:
1. Schema: The outputSchema had no required array and declared all
fields as strict types (e.g. "type": "string"), making every field look
mandatory and non-null.
2. Serialization: model_dump() on TypedDict-derived Pydantic models
emitted None for absent optional fields. A tool returning {"name":
"hello"} produced {"name": "hello", "optional_field": null} which is a
value the schema forbids.
<!-- CURSOR_SUMMARY -->
---
> [!NOTE]
> **Medium Risk**
> Adjusts core schema generation and MCP JSON Schema conversion for
TypedDicts, affecting how tool input/output contracts are emitted and
validated across clients; mistakes could break compatibility or
validation behavior.
>
> **Overview**
> Fixes MCP/engine validation failures for `TypedDict(total=False)`
outputs by ensuring absent optional keys are **omitted from serialized
output** and that emitted schemas correctly describe **required vs
optional** keys.
>
> `arcade-core` now tracks `required_keys`/`inner_required_keys` and
per-field `nullable` in `ValueSchema`, derives required sets from
TypedDict `__required_keys__`, and unwraps `Optional[T]` to support
optional nested TypedDicts; TypedDict-derived Pydantic models now
`model_dump(exclude_unset=True)` to avoid leaking missing fields as
`null`.
>
> `arcade-mcp-server` JSON Schema conversion now emits `required` arrays
(including for arrays of objects), supports `nullable` by generating
`type: [<type>, "null"]` (and `enum` including `None`), and treats
nullable top-level objects as valid unwrapped output schemas. Adds
focused unit/end-to-end tests plus an expanded example server
demonstrating total-false, mixed required/optional, nullable, and
optional-nested TypedDict outputs, and bumps package
versions/dependencies accordingly.
>
> <sup>Reviewed by [Cursor Bugbot](https://cursor.com/bugbot) for commit
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<!-- /CURSOR_SUMMARY -->
Resolves
https://linear.app/arcadedev/issue/TOO-590/add-resources-support-to-server-framework
<!-- CURSOR_SUMMARY -->
---
> [!NOTE]
> **Medium Risk**
> Adds new resource registration/reading semantics (including URI
templates and duplicate/multiple-match policies) and changes JSON Schema
generation for tool I/O, which may affect MCP client compatibility and
runtime behavior across servers.
>
> **Overview**
> **Adds first-class MCP Resources support across `arcade-mcp-server`.**
`MCPApp` can now register resources at build time via
`add_resource`/`@resource` plus convenience `add_text_resource` and
`add_file_resource`, and passes these through to `MCPServer` for startup
loading (including `ResourceTemplate` URIs with `{param}` and `{param*}`
matching).
>
> **Extends `ResourceManager` behavior.** Resource reads now coerce
handler return types (including raw `bytes` to base64
`BlobResourceContents`), support template matching with
overlap/multiple-match detection, and introduce configurable duplicate
handling policies.
>
> **Improves tool schema + MCP Apps linking.** Tool input/output JSON
Schema generation is refactored to recursively expand nested `json`
schemas and ensure `outputSchema` is always an object (wrapping
non-object returns in a `result` property); `MCPApp` also supports
attaching arbitrary tool `_meta` extensions (e.g., `ui.resourceUri`)
applied at server start.
>
> Adds two new example servers (`resources`, `tools_with_output_schema`)
and broad test coverage for resource templates, static/file resources,
meta extensions, and schema wrapping/recursion.
>
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---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
**Implements**: [SEP-2448: server execution telemetry]
(https://github.com/modelcontextprotocol/modelcontextprotocol/pull/2448)
**Description:**
**The Observability Gap (The Problem)**
MCP clients propagate trace context to servers, but server-side
execution remains a black box. The client sees a single tools/call or
resources/read span; everything the server does (auth checks, policy
evaluation, API calls, sub-tool invocations) is invisible. In
cross-organization deployments, clients and servers use separate
observability backends with no shared collector access, making
traditional span export useless.
<img width="1015" height="450" alt="Screenshot 2026-03-23 at 3 43 21 PM"
src="https://github.com/user-attachments/assets/58c817b5-fee6-46a3-9877-d523a25368ad"
/>
**Server Execution Telemetry (The Solution)**
Servers advertise serverExecutionTelemetry and return a curated slice of
their execution spans directly in _meta.otel of the response. Clients
ingest these verbatim OTLP spans into their own collector, stitching
server-side execution into their distributed trace; no shared
infrastructure required. The black box becomes transparent.
<img width="945" height="574" alt="Screenshot 2026-03-23 at 3 43 44 PM"
src="https://github.com/user-attachments/assets/38d97c94-aa73-4e62-9b4e-3264600e5ed0"
/>
.
**Summary:**
Implement MCP serverExecutionTelemetry capability that enables
cross-organization distributed tracing by returning server-side
OpenTelemetry spans to clients inline via _meta.otel.traces.
Server-side (middleware):
- TelemetryPassbackMiddleware intercepts tools/call and resources/read
- ContextVarSpanCollector isolates span collection per-request via
ContextVar
- Propagates traceparent from client request for distributed trace
stitching
- Serializes collected spans to verbatim OTLP JSON (resourceSpans
format), directly POSTable to /v1/traces
- Top-level span filtering by default; full span tree via detailed
opt-in
- Middleware advertises capabilities via get_capabilities() on the
Middleware base class
- Provisional API: FutureWarning emitted until SEP-2448 is ratified
Client-side (reference agent):
- LangChain ReAct agent connects to MCP server via
streamable_http_client with OAuth 2.1
- Detects serverExecutionTelemetry capability at initialization
- Dynamically wraps discovered MCP tools with traceparent propagation
and _meta.otel span request
- Ingests returned server spans into Jaeger (OTLP JSON) and Galileo
(OTLP protobuf)
- Two-act demo: --no-passback (black box) vs default (full server-side
visibility)
Dependencies:
- opentelemetry-api and opentelemetry-sdk added to arcade-mcp-server
Bump arcade-mcp-server version to 1.18.0.
Resolves TOO-201
Documentation PR for this is here:
https://github.com/ArcadeAI/docs/pull/626
<!-- CURSOR_SUMMARY -->
---
> [!NOTE]
> **Medium Risk**
> Changes how environment variables/secrets are discovered and loaded,
which can subtly alter runtime behavior depending on directory structure
and existing env vars; bounded traversal and added tests reduce but
don’t eliminate this risk.
>
> **Overview**
> **Improves `.env` discovery across the MCP server and CLI.** Adds
`find_env_file()` (bounded by the nearest `pyproject.toml` by default)
and switches settings loading, `arcade deploy`, `arcade configure` stdio
env injection, and provider API-key resolution to use it.
>
> Updates dev reload to also watch the discovered `.env` even when it
lives outside the current working directory, adjusts `deploy --secrets
all` to only run when a `.env` was found, and moves the minimal
scaffold’s `.env.example` to the project root with updated
tests/integration checks. Version bumps align examples and top-level
deps with `arcade-mcp-server` `1.17.4` and `arcade-mcp` `1.11.2`.
>
> <sup>Written by [Cursor
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<!-- /CURSOR_SUMMARY -->
---------
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
`arcade-mcp-server` version was not bumped in
https://github.com/ArcadeAI/arcade-mcp/pull/717, so this PR bumps
`arcade-mcp-server`, and then update's `arcade-mcp`'s dependency on
`arcade-mcp-server` by increasing the minimum version
<!-- CURSOR_SUMMARY -->
---
> [!NOTE]
> Bumps arcade-mcp-server to 1.13.0, updates arcade-mcp to 1.6.2, and
raises related dependency minimums (including example auth server).
>
> - **Versions**:
> - Bump `libs/arcade-mcp-server` project version from `1.12.0` to
`1.13.0`.
> - Bump `arcade-mcp` package version from `1.6.1` to `1.6.2`.
> - **Dependencies**:
> - Raise `arcade-mcp` dependency on `arcade-mcp-server` to `>=1.13.0`
in `pyproject.toml` (including `all` extra).
> - Increase example server
`examples/mcp_servers/authorization/pyproject.toml` minimum
`arcade-mcp-server` to `>=1.12.0`.
>
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# Valuable references for the reviewer:
- Docs PR: https://github.com/ArcadeAI/docs/pull/583
- Implements Phase 1 of the following planning doc:
https://linear.app/arcadedev/project/arcade-mcp-supports-mcp-auth-front-door-auth-7cbaa20cb054/overviewhttps://github.com/user-attachments/assets/79ad43fd-f5e8-4793-a1dd-18b35acefdc3
# PR Description
Adds OAuth 2.1 Resource Server authentication to arcade-mcp-server,
enabling HTTP MCP servers to validate Bearer tokens on every request.
This unlocks tool-level authorization and secrets support for HTTP
servers.
- Multiple authorization server support
- Granular token validation options (verify_exp, verify_iat, verify_iss)
- Environment variable configuration
- OAuth discovery metadata endpoint
(/.well-known/oauth-protected-resource)
- Extracts sub claim from token as context.user_id
- Lifts transport restrictions for tools requiring auth/secrets on HTTP
when protected
```python
from arcade_mcp_server import MCPApp
from arcade_mcp_server.resource_server import ResourceServerAuth, AuthorizationServerEntry
resource_server_auth = ResourceServerAuth(
canonical_url="http://127.0.0.1:8000/mcp",
authorization_servers=[
AuthorizationServerEntry(
authorization_server_url="https://auth.example.com",
issuer="https://auth.example.com",
jwks_uri="https://auth.example.com/jwks",
)
],
)
app = MCPApp(name="my_server", version="1.0.0", auth=resource_server_auth)
```
# Testing
Beyond the comprehensive unit tests, I also manually tested end-to-end
with WorkOS Authkit (DCR) and KeyCloak (non-DCR).
# Future Work
- CIMD support
- An `ArcadeResourceServer` to make adding front-door auth super easy
when using Arcade's Auth Server
<!-- CURSOR_SUMMARY -->
---
> [!NOTE]
> Adds OAuth 2.1 front-door auth (JWKS validation + OAuth discovery) and
propagates user identity to tools, enabling auth/secret-requiring tools
over HTTP.
>
> - **Authentication (Front-Door OAuth 2.1)**
> - New `resource_server` module with `ResourceServerAuth`
(multi-authorization-server, metadata) and `JWKSTokenValidator`
(JWKS-based JWT validation) plus granular validation options.
> - ASGI `ResourceServerMiddleware` validates Bearer tokens on every
HTTP request and injects `resource_owner`.
> - OAuth discovery endpoint via FastAPI router at
`/.well-known/oauth-protected-resource[/<path>]`.
> - **Integration**
> - `MCPApp`/`worker` accept `auth`/`resource_server_validator`, mount
middleware, expose discovery; logs accepted auth servers.
> - HTTP transport (`http_streamable`) carries `SessionMessage` with
`resource_owner` from request → session.
> - `Context`/`Session`/`Server` plumb `resource_owner`; `Server`
selects `user_id` preferring token `sub`.
> - **Behavior Changes**
> - HTTP transport restriction lifted for tools requiring
`authorization`/`secrets` when request is authenticated; otherwise
blocked with actionable error.
> - **Configuration**
> - Env-var based auth config via `MCP_RESOURCE_SERVER_*` in
`MCPSettings.ResourceServerSettings`; `.env` auto-load.
> - **Telemetry**
> - Usage tracking records `resource_server_type` on server start.
> - **Examples**
> - New `examples/mcp_servers/authorization` sample server (HTTP auth,
secrets, Reddit tool) with Docker setup.
> - **Tests**
> - Extensive unit tests for validators, middleware, env config,
multi-AS, transport rules, and app integration.
> - **Version**
> - Bump `arcade-mcp-server` to `1.12.0`; minor docstring tweak in
`__init__.py`.
>
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Resolves TOO-152
# PR Description
Consider this PR the result of a full pass through of this repository.
## Add helper for adding tools to an `MCPApp`
You can now add all of the tools in a module to an `MCPApp` via
`app.add_tools_from_module(...)`
## Edit what `arcade new` generates
First, I updated the backend to use hatchling.
Second, the structure generated before this PR was simple, but did not
create a proper Python module.
This hindered developers in the following ways:
1. Difficult to add the tools in your server to an evaluation suite
2. Difficult to add more than one tool to an MCPApp at a time
3. All other niceties that come with being able to import modules
```
# Before
server/
├── .env.example
├── server.py
└── pyproject.toml
```
This PR updates the structure generated such that a valid Python module
is generated:
```
# After
server/
├── pyproject.toml
└── src/
└── server/
├── __init__.py
├── .env.example
└── server.py
```
## Fix Tool Chaining
`self._ctx.server.executor.run(...)` was being called, but `MCPServer`
does not have an instance of `ToolExecutor` (and it's not intended to be
an instance anyways). I updated `Tool.call_raw` to pass the programmatic
tool call through the `MCPServer._handle_call_tool`. This means that the
programmatic tool calls now go through the same steps that a typical
tool call (initiated by the MCP client) would.
This means that **toolA**, which specifies **requirementsA**, is
permitted to call **toolB**, which specifies **requirementsB**, without
needing to explicitly declare or satisfy **requirementsB**. I believe
this is acceptable because the secrets and/or auth token associated with
**toolB's** `Context` are not exposed to **toolA**, and the secrets
and/or auth token associated with **toolA's** `Context` are not exposed
to **toolB**.
## Fix User Elicitation
1. The read & write streams were created with a maximum queue size of 0.
I increased this to 100.
2. I updated `ServerSession`'s run loop to both read messages from the
stream & process them concurrently. This enables server initiated
requests (like user elicitation and progress reporting) to be handled
while tools are being executed. Otherwise, the server initiated requests
would wait for the tool to finish executing and the tool execution would
wait for the server initiated request to finish.
3.
## Fix Progress Reporting
Progress tokens sent by the client were not being stored. Therefore
there was no way to notify a client with progress updates. I am now
storing the `progressToken`, along with other `_meta` sent from the
client, in the `ServerSession`'s `_request_meta`. I am setting
`_request_meta` whenever the `MCPServer` is handling an incoming message
from a client.
## Fix handling of server names with spaces
Before:
Server name: "The simple server name"
Tool name: whisper_secret
Name seen by client: "The_simple_server_name_WhisperSecret"
After
Server name: "The simple server name"
Tool name: whisper_secret
Name seen by client: "TheSimpleServerName_WhisperSecret"
## Add Integration Tests
The stdio integration test is much more comprehensive than the http
integration test. These tests will let me sleep a bit more at night
## Add Example MCP Servers
Example servers for sampling, user-elicitation, progress reporting,
logging, tool chaining, combining prebuilt tools with custom tools, tool
secrets, tool auth, evaluations, and more!
## Add Docker template
Added a Docker template for running an MCP server in Docker (and removed
the old docker stuff)
