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DeepSeek MCP Server

by moyu6027
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Python
Remote

🧠 DeepSeek MCP Server

DeepSeek MCP Server

🚀 Features

Enhance Claude's reasoning capabilities with the integration of DeepSeek R1's advanced reasoning engine. This server enables Claude to tackle complex reasoning tasks by leveraging the reasoning capabilites of deepseek r1 model.

  • DeepSeek R1 (The Brain) acts as the advanced reasoning planner:

    • Plans multi-step logical analysis strategies

    • Structures cognitive frameworks

    • Evaluates confidence and uncertainty

    • Monitors reasoning quality

    • Detects edge cases and biases

  • Claude (The Executor) implements the reasoning plans:

    • Executes the structured analysis

    • Implements planned strategies

    • Delivers final responses

    • Handles user interaction

    • Manages system integrations

Related MCP server: Deepseek R1 MCP Server

🚀 Features

Advanced Reasoning Capabilities

  • Supports intricate multi-step reasoning tasks.

  • Designed for precision and efficiency in generating thoughtful responses.

  • 使用无问芯穹的API

Complete Setup guide

Prerequisites

  • Python 3.12 or higher

  • uv package manager

  • INFINI_API_KEY For DeepSeek (Sign up at 无问芯穹)

  1. Clone the Repository

    git clone https://github.com/moyu6027/deepseek-MCP-server.git
cd deepseek-MCP-server

  2. Ensure UV is Set Up

    • Windows: Run the following in PowerShell:

      powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

    • Mac: Run the following:

      curl -LsSf https://astral.sh/uv/install.sh | sh

  3. Create Virtual Environment

    uv venv
source .venv/bin/activate

  4. Install Dependencies

    uv add "mcp[cli]" httpx

  5. Set Up API Key

    echo "INFINI_API_KEY=your_key_here" > .env

  6. Install the Server

    mcp install server.py -f .env

  7. Configure MCP Server Edit the claude_desktop_config.json file to include the following configuration:

    {
    "mcpServers": {
        "deepseek-mcp": {
            "command": "uv",
            "args": [
                "--directory",
                "PATH_TO_DEEPSEEK_MCP_SERVER",
                "run",
                "server.py"
            ]
        }
    }
}

  8. Run the Server

    uv run server.py

🛠 Usage

Starting the Server

The server automatically starts when used with Claude Desktop. Ensure Claude Desktop is configured to detect the MCP server.

Example Workflow

  1. Claude receives a query requiring advanced reasoning.

  2. The query is forwarded to DeepSeek R1 for processing.

  3. DeepSeek R1 returns structured reasoning wrapped in <ant_thinking> tags.

  4. Claude integrates the reasoning into its final response.

📄 License

This project is licensed under the MIT License. See the LICENSE file for details.

Available Tools

1 tool
reasonB
Process a query using DeepSeek's R1 reasoning engine and prepare it for integration with DeepSeek V3 or claude.

DeepSeek R1 leverages advanced reasoning capabilities that naturally evolved from large-scale 
reinforcement learning, enabling sophisticated reasoning behaviors. The output is enclosed 
within `<ant_thinking>` tags to align with V3 or Claude's thought processing framework.

Args:
    query (dict): Contains the following keys:
        - context (str): Optional background information for the query.
        - question (str): The specific question to be analyzed.

Returns:
    str: The reasoning output from DeepSeek, formatted with `<ant_thinking>` tags for seamless use with V3 or Claude.
ParametersJSON Schema
NameRequiredDescriptionDefault
queryYes

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

B3.4/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It mentions the tool 'leverages advanced reasoning capabilities' and outputs formatted text, but fails to disclose critical behavioral traits such as rate limits, error handling, authentication requirements, or performance characteristics. The description adds some context about the reasoning engine but leaves significant gaps for a tool with potential computational costs.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded, with the core purpose stated in the first sentence. Additional sentences provide useful context about the reasoning engine and output formatting. There is minor redundancy in mentioning 'V3 or Claude' twice, but overall, it's efficient and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (1 parameter with nested structure), no annotations, and an output schema that exists (though not detailed here), the description is reasonably complete. It explains the purpose, parameter semantics, and output format, though it could improve by addressing behavioral aspects like error cases or integration specifics.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds substantial meaning beyond the input schema, which has 0% description coverage and only specifies a generic object. It details that the 'query' parameter is a dict with 'context' (optional background) and 'question' (specific question) keys, clarifying the expected structure and semantics. This compensates well for the schema's lack of documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Process a query using DeepSeek's R1 reasoning engine and prepare it for integration with DeepSeek V3 or claude.' It specifies the verb ('process'), resource ('query'), and technology ('DeepSeek's R1 reasoning engine'), but since there are no sibling tools, it cannot demonstrate differentiation from alternatives.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage by mentioning integration with 'V3 or Claude's thought processing framework,' suggesting it's for preparing reasoning outputs for those systems. However, it lacks explicit guidance on when to use this tool versus alternatives (e.g., direct API calls or other reasoning engines) and does not specify prerequisites or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

B3.4/5.0
Disambiguation5/5

With only one tool named 'reason', there is no possibility of ambiguity or overlap with other tools. The tool has a single, clearly defined purpose of processing queries through DeepSeek's reasoning engine.

Naming Consistency5/5

A single tool cannot demonstrate inconsistency in naming patterns. The tool name 'reason' follows a clear verb-based convention that directly describes its function.

Tool Count2/5

One tool is too few for a server that appears to interface with a complex reasoning engine. While the tool is well-described, a single tool surface severely limits the server's capabilities and suggests an incomplete implementation for the domain.

Completeness2/5

The server has a significant gap in functionality. A reasoning engine server should offer more than just query processing - there are no tools for configuration, status checking, result formatting options, or other typical operations expected from such a service.

Maintenance

ActivityInactive
ResponsivenessNo issues

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