yuntu-mcp-server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| DB_DSN | Yes | Database connection string. MySQL: user:pass@tcp(host:3306)/db?charset=utf8mb4&parseTime=True&loc=Local; or sqlite:///xx.db | |
| MCP_HOST | No | Host for HTTP mode. | 0.0.0.0 |
| MCP_PORT | No | Port for HTTP mode. | 8081 |
| MCP_API_KEY | No | Current tenant's API key. Alternative to YUNTU_API_KEY. | |
| MCP_TRANSPORT | No | Transport mode: 'stdio' (default) or 'http'. | stdio |
| YUNTU_API_KEY | No | Alternative environment variable for MCP_API_KEY. | |
| API_KEY_ENCRYPT_SECRET | Yes | API key encryption secret (>=16 characters), must match the main platform. |
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": true
} |
| logging | {} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| extensions | {
"io.modelcontextprotocol/ui": {}
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| chat_completionB | 调用大模型进行对话,从渠道管理中选择可用渠道并自动扣除 Token。 |
| get_balanceA | 查询当前租户的 Token 余额(需配置 MCP_API_KEY 识别租户)。 |
| list_modelsA | 列出当前可用的所有模型列表。 |
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 3 tools
Each tool has a clearly distinct purpose: chat_completion handles LLM interactions, get_balance checks token quota, and list_models shows available models. No overlap or ambiguity between them.
All three tool names follow a consistent verb_noun pattern in snake_case: chat_completion, get_balance, list_models. The naming is uniform and predictable.
With only 3 tools, the surface is minimal but appropriate for a straightforward LLM gateway. It covers the essential actions (use model, check balance, list models) without unnecessary bloat, though a few more (e.g., channel management) could be expected.
The tool set covers the core user-facing operations for an LLM gateway: chatting, checking balance, and discovering models. It lacks administrative features like managing channels, but for the apparent consumer-focused scope, these are reasonable gaps.