deepseek-agent-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| DEEPSEEK_API_KEY | No | DeepSeek API Key. If not set, the server falls back to ~/.dsh/.credentials.yaml. | |
| DEEPSEEK_BASE_URL | No | API endpoint. | https://api.deepseek.com |
| DEEPSEEK_MCP_MODEL | No | Default model for the delegate_task tool. | deepseek-v4-pro |
| DEEPSEEK_HARNESS_ROOT | No | Path to the deepseek-harness checkout used by run_agent_task. The harness_root parameter takes precedence if provided. |
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
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| delegate_taskA | Send a task or question to the raw DeepSeek model (deepseek-v4-pro) and return its answer. Fast and cheap, but has NO tools and cannot touch files. For work that needs a shell, file edits, or sub-agents, use run_agent_task instead. Stateless: put all context into the task (or the optional system prompt). |
| run_agent_taskA | Run a complete DeepSeek Harness coding agent on a task. The agent has a shell, file read/write/edit, sub-agent delegation, workflow, todo, and session persistence — it can actually modify files in the given workspace. This spawns a one-shot |
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 2 tools
The two tools are clearly distinct: delegate_task is a stateless raw model call, while run_agent_task spawns a full agent with workspace access. The descriptions explicitly contrast them and cross-reference each other, leaving no ambiguity.
Both tools follow a consistent verb_noun pattern (delegate_task, run_agent_task), using a single naming convention that is predictable and readable.
With only 2 tools, the set is slightly under the typical well-scoped range, but given the server's narrow purpose of offering two modes of DeepSeek interaction, the count is reasonable and not excessive.
The tool surface fully covers its stated domain: a simple model query and a full agent execution. No critical operations are missing, though there are no extra lifecycle tools (e.g., cancel/status) that a broader agent workflow might expect.