Sequential Thinking MCP server optimized for AI assistants — Reduce context window tokens by 55.0% while keeping full functionality. Compatible with Claude, ChatGPT, Gemini, Cursor, and all MCP clients.
A token-optimized version of the Sequential Thinking Model Context Protocol (MCP) server.
MCP tool schemas consume significant context window tokens. When AI assistants like Claude or ChatGPT load MCP tools, each tool definition takes up valuable context space.
The original @modelcontextprotocol/server-sequential-thinking loads 1 tools consuming approximately ~1,529 tokens — that's space you could use for actual conversation.
sequential-thinking-slim intelligently groups 1 tools into 1 semantic operations, reducing token usage by 55.0% — with zero functionality loss.
Your AI assistant sees fewer, smarter tools. Every original capability remains available.
| Metric | Original | Slim | Reduction |
|---|---|---|---|
| Tools | 1 | 1 | -0% |
| Schema Tokens | 959 | 118 | 87.7% |
| Claude Code (est.) | ~1,529 | ~688 | ~55.0% |
Benchmark Info
- Original:
@modelcontextprotocol/server-sequential-thinking@2025.12.18- Schema tokens measured with tiktoken (cl100k_base)
- Claude Code estimate includes ~570 tokens/tool overhead
# Claude Desktop - auto-configure
npx sequential-thinking-slim --setup claude
# Cursor - auto-configure
npx sequential-thinking-slim --setup cursor
# Interactive mode (choose your client)
npx sequential-thinking-slim --setupDone! Restart your app to use sequential-thinking.
# Claude Code (creates .mcp.json in project root)
claude mcp add sequential-thinking -s project -- npx -y sequential-thinking-slim@latest
# Windows: use cmd /c wrapper
claude mcp add sequential-thinking -s project -- cmd /c npx -y sequential-thinking-slim@latest
# VS Code (Copilot, Cline, Roo Code)
code --add-mcp '{"name":"sequential-thinking","command":"npx","args":["-y","sequential-thinking-slim@latest"]}'Click to expand manual configuration options
Add to your claude_desktop_config.json:
| OS | Path |
|---|---|
| Windows | %APPDATA%\Claude\claude_desktop_config.json |
| macOS | ~/Library/Application Support/Claude/claude_desktop_config.json |
{
"mcpServers": {
"sequential-thinking": {
"command": "npx",
"args": ["-y", "sequential-thinking-slim@latest"]
}
}
}Add to .cursor/mcp.json (global) or <project>/.cursor/mcp.json (project):
{
"mcpServers": {
"sequential-thinking": {
"command": "npx",
"args": ["-y", "sequential-thinking-slim@latest"]
}
}
}MCPSlim acts as a transparent bridge between AI models and the original MCP server:
┌─────────────────────────────────────────────────────────────────┐
│ Without MCPSlim │
│ │
│ [AI Model] ──── reads 1 tool schemas ────→ [Original MCP] │
│ (~1,529 tokens loaded into context) │
├─────────────────────────────────────────────────────────────────┤
│ With MCPSlim │
│ │
│ [AI Model] ───→ [MCPSlim Bridge] ───→ [Original MCP] │
│ │ │ │ │
│ Sees 1 grouped Translates to Executes actual │
│ tools only original call tool & returns │
│ (~688 tokens) │
└─────────────────────────────────────────────────────────────────┘
- AI reads slim schema — Only 1 grouped tools instead of 1
- AI calls grouped tool — e.g.,
interaction({ action: "click", ... }) - MCPSlim translates — Converts to original:
browser_click({ ... }) - Original MCP executes — Real server processes the request
- Response returned — Result passes back unchanged
Zero functionality loss. 55.0% token savings.
| Group | Actions |
|---|
Plus 1 passthrough tool — tools that don't group well are kept as-is with optimized descriptions.
- ✅ Full functionality — All original
@modelcontextprotocol/server-sequential-thinkingfeatures preserved - ✅ All AI assistants — Works with Claude, ChatGPT, Gemini, Copilot, and any MCP client
- ✅ Drop-in replacement — Same capabilities, just use grouped action names
- ✅ Tested — Schema compatibility verified via automated tests
No. Every original tool is accessible. Tools are grouped semantically (e.g., click, hover, drag → interaction), but all actions remain available via the action parameter.
AI models have limited context windows. MCP tool schemas consume tokens that could be used for conversation, code, or documents. Reducing tool schema size means more room for actual work.
MCPSlim is a community project. It wraps official MCP servers transparently — the original server does all the real work.
MIT
Powered by MCPSlim — MCP Token Optimizer
Reduce AI context usage. Keep full functionality.