jianying-ai-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| JIANYING_EXE | No | 剪映程序路径，用于检测版本 | |
| JIANYING_DRAFT_ROOT | Yes | 剪映草稿根目录 | |
| JIANYING_MCP_TRANSPORT | No | 默认 'stdio'，也可使用 'sse' 或 'streamable-http' | stdio |
| JIANYING_MCP_WORK_ROOT | Yes | 暂存和参考蓝图目录 |
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
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| get_jianying_capabilitiesA | 返回已验证、禁用和首版未纳入的能力，并检测本机剪映版本。规划前必须调用。 |
| analyze_reference_draftA | 读取一个明文参考草稿并提取剪辑蓝图。加密草稿会明确拒绝，不会猜测内容。 |
| build_draftA | 一次提交紧凑编辑清单并生成新草稿。 manifest 结构：
轨道 type 支持 video/audio/text/sticker/effect/filter。时间字段使用 start、duration； 媒体可加 source_start/source_duration、speed。具体字段见 Skill 的 manifest-schema.md。 默认 dry_run=true，只在暂存区完整构建和校验；确认后传 false 发布到剪映草稿目录。 |
| build_from_referenceA | 复制可读参考草稿的剪辑蓝图，并按轨道与片段下标替换素材或文本。 replacements 项：{track_type, track_name? 或 track_index?, segment_index, source, source_start?, source_duration?}。text_replacements 项：{track_name? 或 track_index?, segment_index, text, recalc_style?}。 |
| batch_from_templateB | 基于一个明文模板批量生成草稿。每个 job 包含 name、replacements、text_replacements。 |
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 5 tools
Most tools have clear, distinct purposes: capability discovery, analysis, single build, batch build, and reference-based build. However, analyze_reference_draft and build_from_reference both involve reference drafts and could be confused in some workflows, though descriptions clarify their different roles.
Tool names are snake_case and mostly descriptive, but the pattern is inconsistent. 'get_', 'analyze_', and 'build_' are clear verbs, while 'batch_from_template' lacks a strong verb prefix, and 'build_from_reference' introduces a prepositional modifier absent in 'build_draft'.
With 5 tools, the server is well-scoped for its purpose of generating Jianying drafts through various methods. Each tool addresses a distinct need without redundancy or excessive breadth, fitting comfortably within the ideal 3-15 range.
The tool set covers the core workflow of understanding capabilities, analyzing references, and building drafts from manifests, templates, or references. Minor gaps exist such as no explicit tool for updating or deleting existing drafts, but these are likely outside the server's intended generation-focused scope.