Search 1,000 MCP tools through two interfaces in DeepSeek Harness. Load exact schemas on demand and keep structured results usable across tool calls.
概览
Large tool catalogs take up room before the model starts solving your task. MCP Lens keeps the standing MCP definitions small, finds relevant tools across servers, and preserves the returned data needed by the next call. MCP Lens gives DeepSeek Harness two model-facing tools: 1. mcp_search finds relevant tools and returns their exact input schemas. 2. mcp_call calls a specific server/tool and returns its result, including structured data. The two tool definitions occupy , regardless of catalog size. In the 1,000-tool component fixture, the direct client's definitions occupy . Remote schemas enter the conversation when search returns them. Connections open on demand, and repeated searches reuse the catalog index. The latest version also fixes multi-step workflows: a customer ID returned alongside a text summary stays visible, so the model can use it to look up the customer's order. The tested data flows improved from . Read the September 10 results.
README
以下为原文 README 节选，完整内容请查看原文。
MCP Lens for DeepSeek Harness
English | 简体中文
1,000 MCP tools. Two interfaces. Exact schemas when you need them.
Install · Try the 1,000-tool calculator · See product tests
Large tool catalogs take up room before the model starts solving your task. MCP Lens keeps the standing MCP definitions small, finds relevant tools across servers, and preserves the returned data needed by the next call.
MCP Lens gives DeepSeek Harness two model-facing tools:
mcp_searchfinds relevant tools and returns their exact input schemas.mcp_callcalls a specificserver/tooland returns its result, including structured data.
The two tool definitions occupy 1,114 bytes of JSON, regardless of catalog size. In the 1,000-tool component fixture, the direct client’s definitions occupy 647,962 bytes. Remote schemas enter the conversation when search returns them. Connections open on demand, and repeated searches reuse the catalog index.
The latest version also fixes multi-step workflows: a customer ID returned alongside a text summary stays visible, so the model can use it to look up the customer’s order. The tested data flows improved from 10/12 to 12/12. Read the September 10 results.
This works well for dozens to thousands of tools spread across MCP servers. Search adds a step; for a few tools used on nearly every request, the official direct MCP client is simpler.
Install
Use Node.js ^22.19.0 || >=24.0.0 and Harness 0.1.2-rc.1. As of September 10, 2026, Harness’s npm latest and next tags point to this version.
Build Lens rc.10 from the main branch below. The published npm package is still rc.9, which targets Harness 0.1.0-rc.6.
npm install -g @deepseek-ai/[email protected]
git clone https://github.com/labmimors/dsh-mcp-lens.git
cd dsh-mcp-lens
npm ci --ignore-scripts
npm run build
npm pack --ignore-scripts
dsh plugin --profile web add ./dsh-mcp-lens-0.1.0-rc.10.tgz
dsh plugin uses pnpm. If pnpm is missing from PATH, replace the last command with:
npm exec --yes [email protected] -- dsh plugin --profile web add ./dsh-mcp-lens-0.1.0-rc.10.tgz
If you are keeping an existing Harness 0.1.0-rc.6 installation, use dsh plugin --profile web add [email protected].
Connect your first MCP server
安装
This server does not publish a one-line install command.
Open the repository installation guide 新手？先看 mcpskill.org 教程 →