
Sequential Thinking MCP Server
MCP提供 sequential_thinking 工具,引导模型把复杂问题拆成可修正、可分支的思考步骤,适合规划、分析与需要反复推敲的任务。MCP 官方参考实现。
Sequential Thinking MCP Server
An MCP server implementation that provides a tool for dynamic and reflective problem-solving through a structured thinking process.
Published on npm as @modelcontextprotocol/server-sequential-thinking.
Features
- Break down complex problems into manageable steps
- Revise and refine thoughts as understanding deepens
- Branch into alternative paths of reasoning
- Adjust the total number of thoughts dynamically
- Generate and verify solution hypotheses
Tool
sequential_thinking
Facilitates a detailed, step-by-step thinking process for problem-solving and analysis.
Inputs:
thought(string): The current thinking stepnextThoughtNeeded(boolean): Whether another thought step is neededthoughtNumber(integer): Current thought numbertotalThoughts(integer): Estimated total thoughts neededisRevision(boolean, optional): Whether this revises previous thinkingrevisesThought(integer, optional): Which thought is being reconsideredbranchFromThought(integer, optional): Branching point thought numberbranchId(string, optional): Branch identifierneedsMoreThoughts(boolean, optional): If more thoughts are needed
Usage
The Sequential Thinking tool is designed for:
- Breaking down complex problems into steps
- Planning and design with room for revision
- Analysis that might need course correction
- Problems where the full scope might not be clear initially
- Tasks that need to maintain context over multiple steps
- Situations where irrelevant information needs to be filtered out
In practice, you do not call sequential_thinking directly by hand unless your client exposes raw tool calls. Instead, connect the server to an MCP-aware host and ask the model to think through a problem step by step. The host can then decide to call the tool one or more times while it works.
What it looks like in use
Example prompts that typically benefit from this tool:
Plan a database migration from PostgreSQL 14 to 16, list risks, and revise the plan if downtime exceeds 5 minutes.Debug why this deployment only fails in production and show your reasoning step by step.Compare three architecture options for a file sync engine and branch if one assumption turns out to be wrong.
How to tell it is working
If your host or inspector shows tool activity, you should see repeated calls to sequential_thinking with fields such as:
thoughtthoughtNumbertotalThoughtsnextThoughtNeeded
When the reasoning changes course, you may also see revision or branching fields like isRevision, revisesThought, branchFromThought, or branchId.
Quick manual verification
After installing the server in your MCP host:
- Restart or reload the host so it reconnects to the server.
- Confirm the
sequential_thinkingtool appears in the host's MCP tool list or inspector. - Ask the host to solve a non-trivial problem in a step-by-step way.
- Verify that the host invokes the tool multiple times instead of returning a one-shot answer.
Configuration
Usage with Claude Desktop
Add this to your claude_desktop_config.json:
npx
{
"mcpServers": {
"sequential-thinking": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/server-sequential-thinking"
]
}
}
}
On Windows, use cmd /c to launch npx:
{
"mcpServers": {
"sequential-thinking": {
"command": "cmd",
"args": [
"/c",
"npx",
"-y",
"@modelcontextprotocol/server-sequential-thinking"
]
}
}
}
docker
{
"mcpServers": {
"sequentialthinking": {
"command": "docker",
"args": [
"run",
"--rm",
"-i",
"mcp/sequentialthinking"
]
}
}
}
To disable logging of thought information set env var: DISABLE_THOUGHT_LOGGING to true.
Usage with VS Code
For quick installation, click one of the installation buttons below...
For manual installation, you can configure the MCP server using one of these methods:
Method 1: User Configuration (Recommended)
Add the configuration to your user-level MCP configuration file. Open the Command Palette (Ctrl + Shift + P) and run MCP: Open User Configuration. This will open your user mcp.json file where you can add the server configuration.
Method 2: Workspace Configuration
Alternatively, you can add the configuration to a file called .vscode/mcp.json in your workspace. This will allow you to share the configuration with others.
For more details about MCP configuration in VS Code, see the official VS Code MCP documentation.
For NPX installation:
{
"servers": {
"sequential-thinking": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/server-sequential-thinking"
]
}
}
}
On Windows, use:
{
"servers": {
"sequential-thinking": {
"command": "cmd",
"args": [
"/c",
"npx",
"-y",
"@modelcontextprotocol/server-sequential-thinking"
]
}
}
}
For Docker installation:
{
"servers": {
"sequential-thinking": {
"command": "docker",
"args": [
"run",
"--rm",
"-i",
"mcp/sequentialthinking"
]
}
}
}
Usage with Codex CLI
Run the following:
npx
codex mcp add sequential-thinking npx -y @modelcontextprotocol/server-sequential-thinking
Building
Docker:
docker build -t mcp/sequentialthinking -f src/sequentialthinking/Dockerfile .
License
This MCP server is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more details, please see the LICENSE file in the project repository.
相關資源

Knowledge Graph Memory Server
MCP用本地知识图谱(实体、关系、观察)为 agent 保存跨会话的长期记忆,数据落在本地 JSONL 文件,可随时查询与增删。MCP 官方参考实现。
modelcontextprotocol/servers91.3k
Perplexity API Platform MCP Server
MCP提供 Perplexity 网页搜索、联网问答、深度研究与推理四个工具,可远程接入或本地运行。Perplexity 官方维护,需要 Perplexity API Key。
perplexityai/modelcontextprotocol2.6k
Opik MCP Server
MCPComet 官方维护的 Opik MCP:在对话里查询 LLM 应用的 trace 与 span,记录评分与评论,管理数据集、实验和 prompt 版本。支持 Opik Cloud(API Key 或浏览器登录)与自托管的开源 Opik。
comet-ml/opik-mcp222
Ollama
CLI在本机一条命令下载并运行 Gemma 等开源大模型,提供 REST API 与 Python / JS 库,还能用 ollama launch 让 Claude Code、Codex 等 agent 改用本地模型。
ollama/ollama183k
Claude API
SkillClaude API 与 Anthropic SDK 参考:模型选择与定价、流式输出、工具调用、提示缓存、Managed Agents 等,并提供模型迁移与提示词审计流程。Anthropic 官方技能。
anthropics/skills182k
Agent SDK Dev
Plugin用 /new-sdk-app 交互式搭建 Claude Agent SDK 项目(Python 或 TypeScript),再由校验代理按官方最佳实践检查依赖、配置与代码。Anthropic 官方维护。
anthropics/claude-code151k