wechat-devtools-mcp
Provides integration with WeChat Developer Tools to automate WeChat Mini Program development, testing, debugging, UI inspection, screenshot capture, navigation, and project file management.
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., "@wechat-devtools-mcp打开项目并预览"
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.
WeChat DevTools MCP Server (v0.9.15)
Wraps the WeChat DevTools CLI as an MCP (Model Context Protocol) service, allowing AI in editors to directly invoke WeChat CLI commands, enabling a closed loop for mini program development, testing, debugging, and automation.
[!IMPORTANT] This project adopts a "thin MCP + fat Skill" architecture: the MCP Server provides 7 aggregated APIs, and the accompanying wechat-devtools Skill provides SOP workflows, parameter quick references, and best practices. Both must be used together — without the Skill, the AI will not be able to operate mini programs following the correct workflow.
Published to the official MCP Registry, with one-click installation across platforms (Windows / macOS).
🚀 Installation and Quick Start
Step 1 — Install the MCP Server
uv is recommended, as it automatically handles Python dependencies and provides an isolated execution environment.
pip install uv # 安装 uv(如已安装可跳过)
uv tool install wechat-devtools-mcp --force # 一键安装到全局隔离环境[!WARNING] If you previously installed an older version via
pip install, uninstall it first to avoid version conflicts:pip uninstall wechat-devtools-mcpThe
pip installpath (e.g.Python313/Scripts/) may take precedence over theuv tool installpath (~/.local/bin/), causing the old version to actually run. You can confirm the current version via themcp_versionfield returned bywechat_ide(action='status').
[!WARNING] Version compatibility: ≥0.9.11 supports both mcp 1.x and 2.x (dependency declared as
mcp[cli]>=1.9,<3). ≤0.9.10 is incompatible with mcp ≥2.0 (fresh installs will reportModuleNotFoundError: mcp.server.fastmcp, see #9) — pinned users should upgrade to ≥0.9.11, or append--with "mcp<2"when installing.
[!TIP]
Check the actually running version (≥0.9.13):
wechat-devtools-mcp --version # 零依赖打印实际安装版本;uvx 复用已装环境不自拉最新,此命令可直接确认 uv tool list | grep wechat # 离线确认已安装版本Upgrading the tool: if the editor is running the MCP service, terminate the process before upgrading:
# Bash / CMD taskkill /F /IM "wechat-devtools-mcp*" 2>/dev/null; uv tool upgrade wechat-devtools-mcp# Windows PowerShell Get-Process | Where-Object { $_.ProcessName -like "*wechat-devtools*" } | Stop-Process -Force uv tool upgrade wechat-devtools-mcpOne-click upgrade via Agent:
taskkill /F /IM "wechat-devtools-mcp*" 2>/dev/null; uv tool upgrade wechat-devtools-mcp && npx -y skills add WaterTian/wechat-devtools-mcp/.agents/skills/wechat-devtools
Step 2 — Enable the DevTools Service Port
[!WARNING] This must be enabled manually, otherwise the AI will not be able to send any commands.
Path: DevTools → Settings → Security Settings → Service Port → Enable
💡 You can verify whether the port is enabled via
wechat_ide(action='status')— if it returns a connection failure, the service port has not been enabled yet.
Step 3 — Confirm Required Paths
Obtain the following two absolute paths in advance; you will need to fill them into the editor configuration later:
Path | Windows example | macOS example |
WeChat DevTools CLI |
|
|
Mini program project root |
|
|
macOS users: no need to escape slashes (
/) in JSON config; Windows users must write\as\\.
Step 4 — Editor Configuration
Modify claude_desktop_config.json or mcp_config.json (Antigravity):
{
"mcpServers": {
"wechat-devtools": {
"command": "uvx",
"args": ["wechat-devtools-mcp"],
"env": {
"WECHAT_DEVTOOLS_CLI": "C:\\Program Files (x86)\\Tencent\\微信web开发者工具\\cli.bat",
"WECHAT_PROJECT_PATH": "D:\\Your\\Project\\Path"
}
}
}
}Edit ~/.kiro/settings/mcp.json:
{
"mcpServers": {
"wechat-devtools": {
"command": "uvx",
"args": ["wechat-devtools-mcp"],
"env": {
"WECHAT_DEVTOOLS_CLI": "C:\\Program Files (x86)\\Tencent\\微信web开发者工具\\cli.bat",
"WECHAT_PROJECT_PATH": "D:\\Your\\Project\\Path",
"PYTHONIOENCODING": "utf-8"
},
"autoApprove": [
"wechat_ide", "wechat_build", "wechat_automator", "wechat_inspector",
"wechat_screenshot", "wechat_navigate", "wechat_file"
]
}
}
}Edit ~/.codex/config.toml (global) or .codex/config.toml (project-level):
[mcp_servers.wechat-devtools]
command = "uvx"
args = ["wechat-devtools-mcp"]
[mcp_servers.wechat-devtools.env]
WECHAT_DEVTOOLS_CLI = "C:\\Program Files (x86)\\Tencent\\微信web开发者工具\\cli.bat"
WECHAT_PROJECT_PATH = "D:\\Your\\Project\\Path"You can also add it quickly via CLI:
codex mcp add wechat-devtools \
--env WECHAT_DEVTOOLS_CLI="C:\\Program Files (x86)\\Tencent\\微信web开发者工具\\cli.bat" \
--env WECHAT_PROJECT_PATH="D:\\Your\\Project\\Path" \
-- uvx wechat-devtools-mcpAdd a new Server in the MCP console:
Name:
wechat-devtoolsType:
commandCommand:
uvx wechat-devtools-mcpEnvironment Variables: add
WECHAT_DEVTOOLS_CLIandWECHAT_PROJECT_PATHas above
On Windows, backslashes in paths need to be escaped (
\\).
If you use Claude Code to develop inside a mini program repository, you can create a project-level .mcp.json (automatically follows the repository and applies to collaborators).
Windows — .mcp.json at the repository root:
{
"mcpServers": {
"wechat-devtools": {
"command": "uvx",
"args": ["wechat-devtools-mcp"],
"env": {
"WECHAT_DEVTOOLS_CLI": "C:\\Program Files (x86)\\Tencent\\微信web开发者工具\\cli.bat",
"WECHAT_PROJECT_PATH": "D:\\Your\\Project\\Path"
}
}
}
}macOS — .mcp.json at the repository root:
{
"mcpServers": {
"wechat-devtools": {
"command": "/opt/homebrew/bin/uvx",
"args": ["wechat-devtools-mcp"],
"env": {
"PATH": "/opt/homebrew/bin:/usr/local/bin:/usr/bin:/bin",
"WECHAT_DEVTOOLS_CLI": "/Applications/wechatwebdevtools.app/Contents/MacOS/cli",
"WECHAT_PROJECT_PATH": "/Users/<you>/WeChatProjects/<project>",
"NODE_PATH": "/opt/homebrew/bin/node"
}
}
}
}Three key differences on macOS:
commandmust use the absolute path/opt/homebrew/bin/uvx(Claude Code'sPATHdoes not include Homebrew when spawning child processes)
env.PATHmust be explicitly injected (especially needed when also configuringnpx-based MCPs such as cloudbase / chrome-devtools, otherwisenpx's#!/usr/bin/env nodecannot find Node)
NODE_PATHis recommended to be explicitly specified as a fallback when starting as a daemon
When configuring multiple MCPs at once (cloudbase / chrome-devtools, etc.), handle the
commandabsolute path andenv.PATHfor each server in the same pattern.
Trae v1.3.0+ supports MCP. AI panel → Settings icon in the top right → MCP → Add → Manual configuration, paste the JSON below and save.
Windows:
{
"mcpServers": {
"wechat-devtools": {
"command": "uvx",
"args": ["wechat-devtools-mcp"],
"env": {
"WECHAT_DEVTOOLS_CLI": "C:\\Program Files (x86)\\Tencent\\微信web开发者工具\\cli.bat",
"WECHAT_PROJECT_PATH": "D:\\Your\\Project\\Path"
}
}
}
}macOS:
{
"mcpServers": {
"wechat-devtools": {
"command": "/opt/homebrew/bin/uvx",
"args": ["wechat-devtools-mcp"],
"env": {
"PATH": "/opt/homebrew/bin:/usr/local/bin:/usr/bin:/bin",
"WECHAT_DEVTOOLS_CLI": "/Applications/wechatwebdevtools.app/Contents/MacOS/cli",
"WECHAT_PROJECT_PATH": "/Users/<you>/WeChatProjects/<project>",
"NODE_PATH": "/opt/homebrew/bin/node"
}
}
}
}You can also edit the config file directly:
Windows:
%APPDATA%\Trae\User\globalStorage\mcp.jsonmacOS:
~/Library/Application Support/Trae/User/globalStorage/mcp.json
[!IMPORTANT] You must select the 「Builder with MCP」 agent in the chat box; regular agents do not call MCP tools. It is also recommended to install the wechat-devtools Skill (Step 5) so the AI calls tools in SOP order.
Step 5 — Install the Skill (Required)
[!IMPORTANT] This MCP must be used together with the wechat-devtools Skill. The Skill contains all the SOP workflows, parameter quick references, and troubleshooting guides the AI needs to operate mini programs. Without the Skill installed, the AI can only call bare APIs and cannot automatically execute standardized testing and debugging workflows.
Option 1: npx skills add (Claude Code users)
npx -y skills add WaterTian/wechat-devtools-mcp/.agents/skills/wechat-devtoolsThis pulls it into ~/.claude/skills/, and Claude Code loads it automatically.
Option 2: Manually place it in .agents/skills/ (clients that load from .agents/skills/, such as Trae)
Run this in the mini program project root:
git clone --depth 1 https://github.com/WaterTian/wechat-devtools-mcp.git .wdm-tmp
mkdir -p .agents/skills
cp -r .wdm-tmp/.agents/skills/wechat-devtools .agents/skills/
rm -rf .wdm-tmpThe resulting directory structure:
your-project/
└── .agents/skills/
└── wechat-devtools/
├── SKILL.md # 主指令文件(SOP + 能力映射 + 红线规则)
└── references/
└── tool_reference.md # 7 个聚合 API 完整参数参考[!TIP] Trae users: make sure the Settings → Skills & Commands → Enable .agents skills directory toggle is on (on by default). After saving, refresh and you will see
wechat-devtoolsunder the "Skills → Project" tab.
Related MCP server: harmony-mcp
🛠️ Toolbox Overview
The MCP Server provides 7 aggregated tools covering the full mini program lifecycle:
Tool | Function | Supported actions |
| IDE lifecycle management |
|
| Build and publish |
|
| Automated interaction |
|
| Runtime log collection |
|
| UI screenshots (long image stitching) | — |
| Navigate to pages and collect CDP logs | — |
| Project file reading |
|
For cloud functions and cloud database management, use CloudBase MCP (
manageFunctions/readNoSqlDatabaseContent, etc.), which is more complete and has no IDE dependency.wechat_cloudhas been disabled since v0.9.5.
🧠 Skill Content Details
The Skill lets the AI automatically match and execute standardized operation workflows after receiving natural language instructions:
What you say | What the AI executes |
"Check all pages for errors" | SOP D — Full-page inspection |
"Click the login button and take a screenshot" | SOP B — UI debugging |
"The page is blank, help me troubleshoot" | SOP C — Exception troubleshooting |
"Mock the payment API and test the payment flow" | SOP E — Mock integration testing |
"Test the detail page, what are the parameter names?" | SOP G — Sub-page testing |
"Compare whether points are consistent across pages" | SOP I — Cross-page data validation |
The Skill includes
9 SOP workflows — initialization, UI debugging, exception troubleshooting, full-page inspection, Mock integration testing, network debugging and UI adaptation, sub-page testing, cross-page data validation, parallel data comparison
Capability mapping dictionary — quick index of 7 aggregated tools × all actions
CDP progressive troubleshooting strategy — two stages: concise → full, to control token consumption
Complete parameter reference — required/optional parameters, return examples, and common templates for each action
Troubleshooting manual — common error codes and how to fix them
See Step 5 — Install the Skill for installation instructions
💡 Environment Variables
Variable | Description | Default | Required |
| WeChat DevTools CLI path | — | Yes |
| Default mini program project absolute path | — | Yes |
| CLI command timeout (seconds) |
| No |
| Node.js executable path |
| No |
❓ FAQ
Most common cause: the WeChat DevTools "Service Port" is not enabled.
Go to Settings → Security → Service Port and turn it on. Once enabled, the AI can reconnect without restarting the IDE.
If you opened DevTools manually, it may not be listening on the debug port. Close DevTools and let the AI run wechat_ide(action='open', cdp_enabled=True) to start it in debug mode.
The MCP service in the editor is still running. See the upgrade note under Step 1 — you need to terminate the process before upgrading.
An older version installed via pip install may take precedence. Run pip uninstall wechat-devtools-mcp to remove the old version, then confirm the mcp_version field is the latest via wechat_ide(action='status').
Make sure WECHAT_DEVTOOLS_CLI in the editor configuration's env is set to an absolute path:
Windows: use double backslashes (e.g.
C:\\...\\cli.bat)macOS: standard path
/Applications/wechatwebdevtools.app/Contents/MacOS/cli, no need to escape slashes
When GUI clients (such as Claude Desktop) start MCP, PATH may not include /opt/homebrew/bin. Since MCP v0.9.6, the Homebrew standard path is attempted automatically; if it still fails, set it explicitly in env:
"NODE_PATH": "/opt/homebrew/bin/node"📋 Version History
Version | Description |
0.9.15 | Adapt to DevTools 2.x (Electron) + fix long-standing CDP collection failure: DevTools 2.x switched to Electron (1.06.x Stable still uses NW.js, dual-track compatible, no replacement). macOS startup path auto-detects runtime based on presence of |
0.9.14 | File read path fix + parameter invalidation fix: |
0.9.13 |
|
0.9.12 | Handshake response package version + dependency upper bound: Under mcp 2.x, |
0.9.11 | Compatible with mcp 2.0.0: Official MCP Python SDK 2.0 (released 2026-07-28) removed |
0.9.10 | Fix page_path silent failure: screenshot.js verifies page path match after navigation; returns explicit error when |
0.9.9 | Fix screenshot causing mini-program restart: screenshot.js changes navigation for non-TabBar pages from |
0.9.8 | Fix automator connection stability: daemon.js |
0.9.7 | Fix daemon orphan process residue: daemon.js adds parent process watchdog, checks liveness every 5 seconds with |
0.9.6 | macOS adaptation: |
0.9.5 | Fix latent bug where compile health check permanently failed (ui_debug.js has no |
0.9.4 | Fix switchTab navigation not taking effect (switched to |
Version | Description |
0.9.3 | status adds |
0.9.2 | Fix navigate timeout after compile: daemon connection health check adds 3s timeout protection; automatically invalidates old cached connections and reconnects after compile; navigate currentPage polling adds 2s independent timeout per call; distinguishes HEALTH_CHECK_TIMEOUT and CONNECTION_ERROR error codes |
0.9.1 | Fix AttributeError crash when cdp_enabled=true; add WXML runtime error collection (CDP automatically captures warnings such as template not found after compile) |
0.9.0 | Persistent Node daemon architecture: single daemon process stays resident, NDJSON protocol communication, WS connections reused by port; single daemon.bundle.js replaces 8 independent bundles; tool call latency reduced from 500ms+ to ~3ms; daemon automatically rebuilds connections after compile with zero disconnects |
0.8.0 | Automatically reconnect automator after compile; navigate automatically detects TabBar pages and uses switchTab; screenshot adds full_page/scroll_top/page_path parameters and viewport screenshot mode; page_data adds expected_path polling to prevent stale data; long image stitching dynamic step size fixes content gaps; node_bridge unified connection disconnect retry + 500ms call interval; start port verification increased to 20 times |
0.7.0 | navigate variable scope fix (currentPageTimeout); evaluate supports declaration statements (const/let/var fallback); call_method returns current page path; automator start port polling verification replaces blind waiting; SKILL.md adds efficiency principles, recovery levels, page navigation methods, 6 troubleshooting entries |
0.6.0 | navigate supports query parameters (reLaunch timeout fallback); CDP startup noise filtering (console.assert/__route__/ide:// noise reduction + WXML error protection); compile return value three-way classification + automator invalidation prompt; navigate currentPage polling retry; configurable timeout |
0.5.1 |
|
0.5.0 | Skill SOP comprehensive optimization: adds SOP I/J; adds AppID check and path validation; CDP noise filtering; screenshot stitching fuzzy matching fix |
0.4.1 | Screenshot long page stitching rewrite: fixed region detection, DPR adaptation, dynamic overlap calculation |
0.4.0 | CDP log enhancement, cloud function deployment automatic verification, navigate intelligent diagnostics, adds SOP G/H |
0.3.0 | Major refactor: 44 tools consolidated into 8 APIs; CDP log v2; adds SKILL.md knowledge base |
0.2.6 | README adds OpenAI Codex configuration instructions |
0.2.5 | Adds Kiro editor configuration instructions |
0.2.4 | Screenshot scroll stitching fix: |
0.2.3 | Package optimization: excludes |
0.2.2 | Node.js scripts changed to bundle-only mode |
0.2.1 | Version update and documentation improvements |
0.2.0 | navigate switched to CDP high-definition log collection |
0.1.9 | Fix UTF-8 encoding garbled text |
0.1.8 | Fix Windows Chinese path UnicodeDecodeError |
0.1.7 | Adds core/full toolset presets; adds MCP_DOC.md |
0.1.6 |
|
0.1.5 | Fix Windows stdio blocking issue |
0.1.4 | Adds CDP logs, screenshots, automation and other features |
0.1.3 | Initial version |
Reference Documentation
License
MIT
Available Tools
7 toolswechat_automatorC
小程序自动化交互与运行时查询。 支持 action: start(开启自动化), tap(点击), input(输入), element_info(元素信息), set_data(设置数据), call_method(调用方法), call_wx(调用wx API), mock_wx(Mock wx), evaluate(执行JS), page_stack(页面栈), page_data(页面数据), system_info(系统信息), storage(缓存)。 返回 JSON: {success, data, message, error_code?}。
| Name | Required | Description | Default |
|---|---|---|---|
| params | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
注解均为中性false值,未提供安全画像,描述需要承担完整的副作用披露责任。描述补充了返回JSON结构,但未说明tap/input/set_data等操作可能产生的状态变更、是否需要先执行start,或是否存在权限/运行环境要求,透明性不足。
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
描述结构紧凑、信息密度高:先总述功能,再以冒号分隔列出动作清单,最后给出返回格式,没有冗余或无效信息,且关键的总述放在最前。
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
该工具包含13种action和多个依赖参数,动作间存在耦合关系(如start需要project_path,tap需要selector),而描述只是动作清单,没有阐述各动作的使用场景、先决条件或副作用。即使schema提供了部分属性描述,整体描述对一个高复杂度多动作工具仍然不够完整。
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
顶层params参数在schema中无描述,覆盖率为0%;描述没有对params结构或任何属性进行补充说明,仅用括号标注了action的中文含义,无法补偿参数语义空白。描述没有帮助代理理解如何为不同的action组合正确的参数。
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
描述以具体动词短语'小程序自动化交互与运行时查询'明确工具功能,并列出13种支持的动作及返回格式,使代理能识别这是用于微信小程序自动化交互与运行时查询的工具。但未明确与兄弟工具进行对比,因此不足以达到5分。
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
描述仅列举了支持的动作,没有说明何时应使用该工具而不使用兄弟工具(如 wechat_inspector、wechat_screenshot),也没有提到使用条件或动作之间的先后顺序,缺少任何关于如何选择本工具的指导。
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
wechat_buildAIdempotent
构建、预览、上传小程序及 npm 管理。 支持 action: compile(编译检查), preview(预览), upload(上传), build_npm(构建NPM), cache_clean(清缓存)。 返回 JSON: {success, data, message, error_code?}。
| Name | Required | Description | Default |
|---|---|---|---|
| params | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide idempotentHint=true but no readOnlyHint or destructiveHint. The description states it returns a JSON structure, which adds behavioral context, and mentions that 'upload' requires 'version' (parameter semantics). However, the description does not disclose side effects, such as whether upload publishes to production, whether cache_clean is destructive, or authentication requirements. The idempotentHint is somewhat contradicted by non-idempotent actions like upload, though the description does not explicitly contradict the annotation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact, front-loaded with the core purpose and action list, and ends with the return format. No wasted words; fits within a few lines.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with a rich action enum and many parameters, the description covers the main actions and the return structure, but does not elaborate on prerequisites, side effects, or error handling. With 11 parameters and 5 actions, the description leaves about half the behavioral context to the schema and annotations. Adequate but with clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the parameter descriptions in the schema are quite detailed (e.g., role of cdp_port, clean_type, version for upload). The tool description adds the grouping of actions and the JSON return shape, but most parameter explanations come from the schema itself, not the description. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action is a build/preview/upload tool for WeChat mini-programs and lists the specific actions it supports. It distinguishes itself from siblings by covering build-related operations, though it doesn't explicitly compare to sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage contexts (build operations, npm management) but does not provide explicit when-to-use or when-not-to-use guidance. It lacks alternatives or exclusions, though the action enum provides some guidance on what each action does.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
wechat_fileARead-onlyIdempotent
读取小程序项目文件和结构信息。 支持 action: project_info(项目完整信息), list_pages(页面列表), read_page(读取页面源码), read_file(读取单个文件)。 返回 JSON: {success, data, message, error_code?}。
| Name | Required | Description | Default |
|---|---|---|---|
| params | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already disclose readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds the JSON return structure ({success, data, message, error_code?}) and enumerates the supported actions, which gives further behavioral clarity. No contradiction with annotations exists, and the description complements the safety profile without duplicating it.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single paragraph that front-loads the purpose, lists the actions, and states the return format. Every sentence contributes value, and there is no filler. It is concise and well-structured, though slightly compact for the amount of information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present, the description need not detail return fields extensively, and it does provide the top-level JSON shape. However, it does not explain parameter relationships or optionality (e.g., which paths are required for which actions), which an agent would need to call the tool correctly. Given the tool's multi-action nature and optional parameters, this is a noticeable gap, though not critical for a read-only tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description explains the meaning of the 'action' enum values (project_info, list_pages, read_page, read_file) but does not clarify the roles of 'file_path', 'page_path', or 'project_path', nor the dependencies (e.g., read_page requires page_path). The schema provides descriptions for each field, but the context signal indicates 0% description coverage, meaning the tool description does not substitute for that. The description only partially compensates for the low coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool reads WeChat mini program project files and structure, and lists four distinct actions (project_info, list_pages, read_page, read_file). This distinguishes it from sibling tools like wechat_navigate or wechat_screenshot, which have different purposes. The verb '读取' and resource '小程序项目文件' make the purpose explicit and unmistakeable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool versus alternatives, but the available actions imply its scope (reading project files). It does not mention exclusions or conditions that would steer an agent to a sibling tool. Context is clear but there is no comparative guidance, so it remains adequate rather than optimal.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
wechat_ideBIdempotent
微信开发者工具 IDE 生命周期管理。 支持 action: open(打开IDE/项目), login(扫码登录), is_login(检查登录), close(关闭项目), quit(退出IDE), status(环境诊断)。 返回 JSON: {success, data, message, error_code?}。
| Name | Required | Description | Default |
|---|---|---|---|
| params | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide idempotentHint=true and destructiveHint=false, and the description does not contradict them. The description adds a return envelope format ({success, data, message, error_code?}) and action semantics, but it does not disclose side effects such as launching a GUI application, blocking on QR code scanning, or requiring the IDE to be installed/running. With annotations covering safety, a 3 is appropriate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is exactly two sentences: the first states the overall purpose, the second lists actions and the return format. There is no filler, repetition, or unnecessary detail. The structure is front-loaded and every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a multi-action tool with 10 parameters, and the description does not map parameters to specific actions (e.g., open requires project_path, login uses qr_format/result_output). It also omits prerequisites and likely failure modes. The one-line JSON envelope covers the output shape, but for a lifecycle manager of this complexity, the description is incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool description only adds semantic meaning to the action enum by explaining what each action does. It says nothing about project_path, port, qr_format, qr_output, cdp_port, or result_output, which are all documented in the schema but not compensated for at the description level. Given schema_description_coverage is 0%, the description should carry more weight for parameters but does not.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as WeChat Developer Tools IDE lifecycle management and enumerates six specific actions (open, login, is_login, close, quit, status) with brief semantic labels for each, such as '打开IDE/项目' and '扫码登录'. This makes it easy to distinguish from sibling tools like wechat_build or wechat_inspector, which target different aspects of the WeChat toolchain.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit guidance on when to use this tool versus siblings. It does not mention alternatives, exclusions, prerequisites, or conditions such as 'use wechat_build for compilation' or 'use wechat_inspector for debugging'. The action list implies capability but does not help an agent decide between lifecycle management and other tool categories.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
wechat_inspectorARead-onlyIdempotent
采集小程序运行时日志和异常。 支持 action: console(automator端口采集console日志和JS异常), cdp(通过CDP协议采集WXML警告、渲染层报错、废弃API提示等底层日志)。 cdp action 需先以 cdp_enabled=true 打开项目,确保端口 9222 可用。 返回 JSON: {success, data: {logs, summary}, message}。
| Name | Required | Description | Default |
|---|---|---|---|
| params | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so safety is covered. The description adds concrete behavioral context: two acquisition protocols, the cdp pre-condition, and the JSON response envelope {success, data:{logs, summary}, message}. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Four sentences, no filler; purpose is front-loaded and the action/prerequisite/return-format sections are each one line. Easily scannable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Between the description, detailed nested parameter docs, and the available output schema, an agent has what it needs to invoke either action. Minor gap: the cdp port prerequisite is stated as a fixed 9222 rather than tied to the cdp_port parameter, but the default matches.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already documents all nested parameters with descriptions, including duration behavior and log_type. The description adds semantic value by explaining what each action value means and reiterating the cdp port requirement, which the bare schema enum does not provide.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Opens with '采集小程序运行时日志和异常' – a specific verb and object. The two actions (console vs cdp) map to distinct log sources, which separates it from siblings like wechat_build or wechat_screenshot. No ambiguity about what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states that the cdp action requires opening the project with cdp_enabled=true and a usable port 9222, and separates what each action collects (console/JS exceptions vs WXML/render/deprecated-API logs). It does not name sibling alternatives or exclusions, but the internal action guidance is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
wechat_screenshotARead-onlyIdempotent
实时捕获当前小程序模拟器的界面截图。 默认支持截取长图,自动滚动并拼接。 output_path 可选,留空则自动保存到项目目录下 screenshots/ 文件夹。 返回 JSON: {success, data: {path, width, height, segments}, message}。
| Name | Required | Description | Default |
|---|---|---|---|
| params | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (readOnlyHint, idempotentHint, destructiveHint), the description reveals that the tool auto-scrolls and stitches long screenshots by default, that output_path can be omitted to save to screenshots/, and that the response is a JSON object with success, data.path/width/height/segments, and message. These behavioral details help the agent anticipate side effects and response shape. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Four short sentences, each adding new information: purpose, long-screenshot default, output_path default, return format. The most important action and defaults are front-loaded. No redundant or marketing language.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only screenshot tool with a rich schema and an output schema, the description covers the key defaults and return format. It does not mention prerequisites like the simulator being open or the meaning of 'segments', but these are minor given the existing schema and annotations. The description is sufficient for an agent to invoke the tool correctly in most cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The context signal reports 0% schema description coverage, so the description must compensate, but it only details output_path's default location and implicitly full_page's default. Parameters like overlap, auto_port, page_path, and scroll_top are not explained in the description, requiring the agent to inspect the nested $defs. The $defs do contain descriptions, which mitigates this, but the description itself adds little parametric meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: '实时捕获当前小程序模拟器的界面截图' (capture the current mini-program simulator interface screenshot in real-time). It further clarifies the long-screenshot default and references the output path and return JSON, leaving no doubt about the tool's function. This clearly distinguishes it from sibling tools like wechat_build or wechat_navigate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context that this is for capturing screenshots of the simulator and mentions default long-screenshot behavior. It does not, however, name any sibling tools or state when to prefer this over wechat_inspector or wechat_automator. A brief 'use this when you need a screenshot' would have been stronger, but the context is unambiguous enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
7 tool updates
v0.9.16- First observed
wechat_automator - First observed
wechat_build - First observed
wechat_file - First observed
wechat_ide - First observed
wechat_inspector - First observed
wechat_navigate - First observed
wechat_screenshot
TDQS
The seven tools are mostly organized by clear domains (IDE lifecycle, build, automation, logs, screenshot, navigation, file access). However, wechat_inspector and wechat_navigate both collect CDP/runtime logs, which could create ambiguity when an agent simply needs log data.
All tools share the wechat_ prefix and snake_case, making the family recognizable, but the second segment mixes nouns (ide, automator, inspector, screenshot, file) with verbs (build, navigate). The internal action lists are consistently verb-based, so the deviation is minor.
Seven tools is well-scoped for a WeChat DevTools automation server. Each tool bundles related actions under a single interface, avoiding both fragmentation and a monolithic do-everything tool.
The surface covers the main lifecycle: open/login/close, compile/preview/upload, automation interaction, log collection, screenshots, navigation, and file/project reads. Minor gaps remain, such as no explicit stop action for automation sessions and no project creation, but core workflows have no dead ends.
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