JoyCode MCP Server - FOP Workflow Assistant
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| load_configC | 加载FOP配置文件 - 保留原有配置加载机制 |
| get_workflow_configB | 获取工作流配置 - 支持stage1/2/3阶段 |
| show_config_summaryB | 显示配置摘要 - 完整显示所有配置信息 |
| get_smart_retrieval_configB | 获取智能检索配置 - 包含代码分析优化策略 |
| execute_workflow_stageC | 执行工作流阶段 - 完整执行PRD分析/代码生成/流程图生成 |
| get_file_naming_rulesC | 获取文件命名规则 - 按照FOP规范生成文件名 |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 6 tools
The tools have some distinct purposes (e.g., execute_workflow_stage vs. get_file_naming_rules), but there is notable overlap between configuration-related tools like get_workflow_config, load_config, and show_config_summary, which could cause confusion about which to use for configuration tasks. The descriptions help differentiate them, but the boundaries are not entirely clear.
Tool names follow a consistent verb_noun pattern (e.g., execute_workflow_stage, get_file_naming_rules) with all using snake_case, making them predictable and readable. There are minor deviations in verb choice (e.g., 'load' vs. 'get' vs. 'show'), but the overall pattern is maintained.
With 6 tools, the count is reasonable for a workflow assistant focused on FOP (File Organization and Processing), as it covers execution, configuration, and retrieval aspects. It is slightly lean but appropriate for the apparent scope, though it might benefit from additional tools for more comprehensive workflow management.
The toolset covers core areas like workflow execution, configuration loading, and rule retrieval, but there are notable gaps in lifecycle coverage. For example, there are no tools for updating or deleting configurations, managing workflow stages beyond execution, or handling errors, which could limit agent effectiveness in dynamic scenarios.