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Deepseek Thinker MCP Server

by ruixingshi
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JavaScript
Hybrid

Deepseek Thinker MCP Server

A MCP (Model Context Protocol) provider Deepseek reasoning content to MCP-enabled AI Clients, like Claude Desktop. Supports access to Deepseek's thought processes from the Deepseek API service or from a local Ollama server.

Core Features

  • 🤖 Dual Mode Support

    • OpenAI API mode support

    • Ollama local mode support

  • 🎯 Focused Reasoning

    • Captures Deepseek's thinking process

    • Provides reasoning output

Related MCP server: Deepseek MCP Server

Available Tools

get-deepseek-thinker

  • Description: Perform reasoning using the Deepseek model

  • Input Parameters:

    • originPrompt (string): User's original prompt

  • Returns: Structured text response containing the reasoning process

Environment Configuration

OpenAI API Mode

Set the following environment variables:

API_KEY=<Your OpenAI API Key>
BASE_URL=<API Base URL>

Ollama Mode

Set the following environment variable:

USE_OLLAMA=true

Usage

Integration with AI Client, like Claude Desktop

Add the following configuration to your claude_desktop_config.json:

{
  "mcpServers": {
    "deepseek-thinker": {
      "command": "npx",
      "args": [
        "-y",
        "deepseek-thinker-mcp"
      ],
      "env": {
        "API_KEY": "<Your API Key>",
        "BASE_URL": "<Your Base URL>"
      }
    }
  }
}

Using Ollama Mode

{
  "mcpServers": {
    "deepseek-thinker": {
      "command": "npx",
      "args": [
        "-y",
        "deepseek-thinker-mcp"
      ],
      "env": {
        "USE_OLLAMA": "true"
      }
    }
  }
}

Local Server Configuration

{
  "mcpServers": {
    "deepseek-thinker": {
      "command": "node",
      "args": [
        "/your-path/deepseek-thinker-mcp/build/index.js"
      ],
      "env": {
        "API_KEY": "<Your API Key>",
        "BASE_URL": "<Your Base URL>"
      }
    }
  }
}

Development Setup

# Install dependencies
npm install

# Build project
npm run build

# Run service
node build/index.js

FAQ

Response like this: "MCP error -32001: Request timed out"

This error occurs when the Deepseek API response is too slow or when the reasoning content output is too long, causing the MCP server to timeout.

Tech Stack

  • TypeScript

  • @modelcontextprotocol/sdk

  • OpenAI API

  • Ollama

  • Zod (parameter validation)

License

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

Available Tools

1 tool
get-deepseek-thinkerD

think with deepseek

ParametersJSON Schema
NameRequiredDescriptionDefault
originPromptYesuser's original prompt

TDQS

D1.7/5.0
Behavior1/5

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

No annotations are provided, so the description carries full burden for behavioral disclosure. 'think with deepseek' reveals nothing about whether this is a read/write operation, what permissions are needed, whether it has side effects, rate limits, or what kind of response to expect. It's completely opaque about behavioral characteristics.

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

Conciseness2/5

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

While technically concise with just three words, this is under-specification rather than effective conciseness. The description fails to convey meaningful information, so its brevity is a deficiency rather than a virtue. Every word should earn its place, but here the words don't provide useful content.

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

Completeness1/5

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

For a tool with no annotations and no output schema, the description is completely inadequate. It doesn't explain what the tool does, when to use it, what behavior to expect, or what results it returns. The single parameter is documented in the schema, but the overall context for using this tool is missing entirely.

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

Parameters3/5

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

Schema description coverage is 100%, with the single parameter 'originPrompt' clearly documented as 'user's original prompt'. The description adds no additional parameter information beyond what the schema provides, which is acceptable given the high schema coverage. The baseline of 3 is appropriate when the schema does the documentation work.

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

Purpose2/5

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

The description 'think with deepseek' is a tautology that restates the tool name rather than explaining what the tool actually does. It doesn't specify what resource is being accessed or what operation is performed. While it hints at some thinking/processing function, the purpose remains vague and undefined.

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

Usage Guidelines1/5

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

The description provides absolutely no guidance about when to use this tool, what problems it solves, or what context it's appropriate for. There are no sibling tools mentioned, but even for a standalone tool, this offers no usage context or prerequisites.

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

C2.2/5.0
Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool's purpose is clearly distinct by default.

Naming Consistency5/5

The single tool name 'get-deepseek-thinker' follows a consistent pattern, and with no other tools to compare, there is no inconsistency in naming conventions.

Tool Count2/5

A single tool is too few for most server purposes, as it limits functionality and suggests a thin or incomplete surface. This is borderline for typical server scopes, leaning towards inadequacy.

Completeness1/5

The server's purpose appears to be 'think with deepseek,' but with only one tool, the surface is severely incomplete. There are obvious gaps, such as no way to configure, modify, or manage thinking processes, leading to dead ends for agents.

Maintenance

ActivityInactive
ResponsivenessSyncing

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Related MCP Connectors

Related MCP Servers

  • MCP Ollama Consult Server

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    Enables consulting with local Ollama models for reasoning from alternative viewpoints. Supports sending prompts to Ollama models and listing available models on your local Ollama instance.
    5
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  • Deepseek MCP Server

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    MCP server for DeepSeek AI models (Chat + Reasoner). Supports multi-turn sessions, model fallback with circuit breaker, function calling, thinking mode, JSON output, multimodal input, and cost tracking.
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  • mcp-server-deepseek

    tizee
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    A Model Context Protocol (MCP) server that provides access to DeepSeek-R1's reasoning capabilities, allowing non-reasoning models to generate better responses with enhanced thinking.
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