MCP Surface Lint
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCP Surface LintLint my tool surface for silent failures."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
title: MCP Surface Lint emoji: 🔎 colorFrom: indigo colorTo: gray sdk: gradio sdk_version: 6.20.0 app_file: app.py pinned: false license: mit short_description: Find where an MCP tool surface lets a caller fail silently tags:
mcp
mcp-server
developer-tools
static-analysis
MCP Surface Lint
Static checks over an MCP tool surface. Every rule answers one question:
Could a caller do the wrong thing and get no error back?
A tool that crashes on bad input is fine. A tool that accepts bad input and returns something plausible is the expensive kind of broken, because neither the caller nor the person reading the transcript has any signal that it happened.
Paste a tools/list response, get back the specific places that can happen.
This app is also an MCP server, so an agent can lint an agent interface without going through the UI.
Using it as an MCP server
Launched with demo.launch(mcp_server=True). Point a client at:
https://<space-host>/gradio_api/mcp/sseTwo tools are published:
Tool | Purpose |
| Run every rule over a surface, return findings with severities |
| Enumerate the checks, their ids, and their severities |
The UI event handlers are deliberately excluded with api_name=False. Without
that, Gradio also publishes analyse, analyse_1, and explain as tools: a
duplicate-name pair plus a handler taking a gr.State that cannot survive a tool
call. This linter flags all three patterns, so shipping them would be a poor look.
The rules
Id | Severity | Catches |
MCP001 | high | Tool has no description |
MCP002 | low | Description too short to distinguish from a neighbour |
MCP003 | high | No |
MCP004 | high | Parameter with no description |
MCP005 | high | Parameter with no declared type |
MCP006 | medium | String parameter that is really a closed set, with no |
MCP007 | high | Properties declared but no |
MCP008 | low | Numeric parameter with no bounds |
MCP009 | medium | Unconstrained object parameter |
MCP010 | medium | Description never says what failure looks like |
MCP011 | high | Destructive verb with no guard parameter and no warning |
MCP012 | medium | Two tools a caller cannot choose between by name |
MCP013 | medium | Two tools sharing an identical description |
Names are compared after crude stemming, because list_user_records and
list_users_record are the same tool as far as a caller is concerned and raw
token comparison misses that entirely.
What it found in its own surface
Pointed at its own published schema, the linter returns exactly one finding, and it is not in this repo:
[high] MCP007 lint_tool_surface: Schema declares properties but no 'required' listGradio's get_input_schema builds {"type": "object", "properties": {...}} and
never emits a required array. The information is already there: the same
parameter dicts it iterates carry parameter_has_default, and Gradio's own
gradio skills command uses that field to mark a parameter required. The
practical effect is that every Gradio MCP server publishes tools whose
arguments all look optional, so a caller that omits a mandatory one produces a
schema-valid call.
Reported upstream as gradio-app/gradio#13670.
Running locally
pip install -r requirements.txt
python app.pyTests:
python -m pytest -qRules are only worth what their tests are worth, so there is also a mutation matrix. It neuters each rule in turn and records which tests fail. A rule with no failing test is either dead code or unguarded, and you cannot tell which without looking:
python mutation_check.pyIt refuses to report anything unless the baseline suite is green first, and it
disables bytecode caching, because every mutated file is the same length and
CPython validates a cached .pyc on (mtime, size). Inside one second that pair
does not change, so the interpreter happily re-imports the previous mutation's
bytecode and the whole matrix reports the wrong rule's result.
License
MIT.
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