原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

Partuno — DigiKey & Mouser MCP Server

作者:JPMarhefka版本 4.0.1i★ –i在你的电脑上运行
注册名称io.github.JPMarhefka/partuno

安装

概览

作者提供的说明(英文原文)

DigiKey and Mouser MCP server for component research, BOM analysis, and sourcing.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 搜索与 AI 记忆
  • 你需要填写:DIGIKEY_ACCESS_TOKEN, DIGIKEY_CLIENT_ID, DIGIKEY_CLIENT_SECRET, MOUSER_SEARCH_API_KEY, MOUSER_ACCOUNT_API_KEY

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 需要你自己填写: DIGIKEY_ACCESS_TOKEN, DIGIKEY_CLIENT_ID, DIGIKEY_CLIENT_SECRET, MOUSER_SEARCH_API_KEY, MOUSER_ACCOUNT_API_KEY

标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。

你需要

  • PyPI已安装 Python 的 uv(用于 uvx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "partuno": {
      "command": "uvx",
      "args": [
        "partuno",
        "partuno-mcp"
      ],
      "env": {
        "DIGIKEY_ACCESS_TOKEN": "your-value",
        "DIGIKEY_CLIENT_ID": "your-value",
        "DIGIKEY_CLIENT_SECRET": "your-value",
        "MOUSER_SEARCH_API_KEY": "your-value",
        "MOUSER_ACCOUNT_API_KEY": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add partuno --env DIGIKEY_ACCESS_TOKEN=your-value --env DIGIKEY_CLIENT_ID=your-value --env DIGIKEY_CLIENT_SECRET=your-value --env MOUSER_SEARCH_API_KEY=your-value --env MOUSER_ACCOUNT_API_KEY=your-value -- uvx partuno partuno-mcp

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "partuno": {
      "command": "uvx",
      "args": [
        "partuno",
        "partuno-mcp"
      ],
      "env": {
        "DIGIKEY_ACCESS_TOKEN": "your-value",
        "DIGIKEY_CLIENT_ID": "your-value",
        "DIGIKEY_CLIENT_SECRET": "your-value",
        "MOUSER_SEARCH_API_KEY": "your-value",
        "MOUSER_ACCOUNT_API_KEY": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "partuno": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "partuno",
        "partuno-mcp"
      ],
      "env": {
        "DIGIKEY_ACCESS_TOKEN": "your-value",
        "DIGIKEY_CLIENT_ID": "your-value",
        "DIGIKEY_CLIENT_SECRET": "your-value",
        "MOUSER_SEARCH_API_KEY": "your-value",
        "MOUSER_ACCOUNT_API_KEY": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

需要你填写的值

  • DIGIKEY_ACCESS_TOKEN 机密 env
    Optional DigiKey bearer token for local mode.
  • DIGIKEY_CLIENT_ID 机密 env
    DigiKey OAuth client ID for the operator's integration.
  • DIGIKEY_CLIENT_SECRET 机密 env
    DigiKey OAuth client secret for the operator's integration.
  • MOUSER_SEARCH_API_KEY 机密 env
    Optional Mouser Search API key for catalog workflows.
  • MOUSER_ACCOUNT_API_KEY 机密 env
    Optional Mouser Account API key for order-history and Cart workflows.

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 JPMarhefka 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“搜索与 AI 记忆”中的其他服务器比较i

  • 星标数多于此分类中其他 7275 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 7275 个服务器的 30% 更新
  • 基础检查结果等于或优于此分类中其他 7275 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Partuno — DigiKey & Mouser MCP Server 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

你需要填写:DIGIKEY_ACCESS_TOKEN, DIGIKEY_CLIENT_ID, DIGIKEY_CLIENT_SECRET, MOUSER_SEARCH_API_KEY, MOUSER_ACCOUNT_API_KEY

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(4.0.1)于3个月前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。

有什么可以替代它?

同一分类中有:Context7, Codebase Memory, Exa

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Context7

作者:upstash

Up-to-date docs for AI agents

电脑或云端★ 64,224MIT昨天更新
安装

Codebase Memory

作者:DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

在你的电脑上运行★ 48,148MIT21天前更新
安装

Exa

作者:exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

在云端运行★ 5,213MIT上个月更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

Partuno - DigiKey & Mouser MCP Server

Local-first component intelligence for MCP

Partuno is an open-source, provider-neutral, local-first Model Context Protocol (MCP) server for electronic component research, BOM analysis, sourcing comparison, and safe distributor workflows. Connect an AI assistant to your own DigiKey and Mouser credentials without shared credentials or autonomous ordering, while keeping evidence, normalized attributes, and explicit uncertainty visible.

Partuno was initially developed as a native MCP server. Native MCP is the recommended connection because it works as an app in ordinary ChatGPT conversations and exposes richer tool annotations. Existing Custom GPT Action endpoints remain available for backward compatibility, including /action-openapi.json.

Partuno does not provide a shared public server or shared distributor

credentials. The Render configuration is an optional reference deployment

for an operator's own single-user instance.

Start here

Use the published package (recommended)

Partuno is published on PyPI and listed in the official MCP Registry. The recommended local MCP launcher is:

uvx --from partuno partuno-mcp

This downloads the current published release and runs the default local stdio transport. To pin the current release exactly, use:

uvx --from 'partuno==4.0.1' partuno-mcp

MCP clients that accept a local command can use uvx with these arguments:

{

"command": "uvx", "args": ["--from", "partuno", "partuno-mcp"] }

Keep your operator-owned DigiKey and Mouser credentials in the MCP client's environment. See the local deployment guide for the supported variables and the native MCP setup guide for operator-owned remote deployments. For a hosted directory listing, see Partuno on Glama.

Install with pip

If uvx is not available, install the published package into an existing Python environment:

python3 -m pip install partuno

partuno-mcp

Develop from source

Use a checkout only when contributing, running unreleased changes, or needing the repository's .env.example and test suite:

git clone https://github.com/JPMarhefka/partuno.git

cd partuno python3 -m venv .venv source .venv/bin/activate python -m pip install -r requirements.txt cp .env.example .env set -a source .env set +a python -m partuno

See the local deployment guide for loopback HTTP and source-checkout details.

Self-host a remote MCP server

If your client requires a reachable HTTPS endpoint, deploy your own instance with your own provider accounts, OAuth application, signing key, rate limits, and hosting budget. Start with the Render reference deployment, or use the Docker and Azure guides. There is no shared Partuno endpoint intended for public use.

Use the existing Action compatibility surface

Custom GPT Actions are retained for existing integrations. The Action/OpenAPI surface is not the primary architecture; use native MCP for new connections. The Action setup details are documented in MCP setup.

What Partuno does

  • Searches and inspects electronic components across DigiKey and Mouser.
  • Normalizes manufacturer part numbers, units, compliance values, and common distributor-specific attribute names.
  • Compares exact component offers at a requested quantity, including price breaks, minimum order quantities, order multiples, availability, and partial provider failures.
  • Recommends components against hard requirements while preserving meets, does_not_meet, and unknown evidence states.
  • Analyzes BOMs for stock, lifecycle, compliance, pricing, tariffs, lead time, and substitute candidates.
  • Supports bounded account and project workflows such as read-only order history, list and quote previews, receiving reconciliation, and carefully confirmed mutations where the provider supports them.

See the capability reference for the current scope and the safety boundary for each workflow.

DigiKey MCP server

Partuno can run as a local-first DigiKey MCP server for component search, product research, current pricing and availability, lifecycle checks, MyLists, quotes, receiving reconciliation, and other bounded account workflows. The DigiKey MCP server guide covers setup, supported workflows, and the provider-specific safety boundaries.

Mouser MCP server

Partuno also provides a Mouser MCP server surface for catalog search, exact offer comparison, read-only order history, and preview-confirmed Cart workflows. The Mouser MCP server guide explains the separate operator-owned Mouser credentials and what the server does and does not execute.

Electronics BOM MCP server

Use Partuno as an electronics BOM MCP server to consolidate duplicate rows, resolve exact products, estimate current merchandise cost, check stock and lifecycle risk, inspect compliance and lead-time signals, and find substitutes or alternate packaging. See the electronics BOM MCP server guide for a complete read-only example and known limitations.

AI component sourcing

Partuno turns a natural-language engineering request into a traceable sourcing workflow. Recommendations preserve meets, does_not_meet, and unknown evidence states, so missing or ambiguous attributes are not silently treated as qualified requirements. The natural-language examples show the intended interaction style.

DigiKey vs Mouser comparison

For an exact comparison, Partuno matches manufacturer and MPN identity first, then compares requested-quantity pricing, minimum order quantity, order multiples, purchasable quantity, availability, and manufacturer lead time. If a provider fails or returns incomplete evidence, the result remains partial instead of inventing a winner. See the DigiKey vs Mouser comparison guide.

What Partuno does not do

  • It does not supply DigiKey or Mouser credentials.
  • It does not create a shared multi-tenant credential pool.
  • It does not silently turn unknown product data into a pass.
  • It does not submit distributor orders.
  • It does not bypass provider quotas, terms, authentication, or rate limits.

See it in action

Featured example: choose a component for a 3.3 V design

Once Partuno is connected, a user can simply ask:

I’m choosing a dual op amp for a 3.3 V circuit. Find a few LM358-family

options that can operate at 3.3 V, are RoHS compliant, normally stocked, and available in a quantity of 10. Show the evidence behind each recommendation and keep uncertain data clearly marked.

Partuno turns that plain-language request into a provider-aware result with qualified, unverified, and rejected candidates; normalized voltage and compliance evidence; cross-distributor availability; quantity pricing; and a Pareto shortlist. It does not silently treat missing specifications as a pass.

This is a roughly 10-second prompt-to-result capture that shows the request and a smooth response scroll. Prices, stock, and lead times are live provider data and can change.

See more natural-language examples for comparison, product research, BOM review, and safe account-preview workflows.

Documentation

TopicGuide
Capabilities and safety boundariesCapability reference
Native MCP connectionMCP setup
Local stdio or loopback HTTPLocal deployment
Docker deploymentDocker deployment
Operator-owned Render deploymentRender reference
Azure deploymentAzure deployment
Security and credential handlingSecurity guide
Offline and live validationTesting guide and validation notes
Natural-language usage examplesExamples
DigiKey, Mouser, and BOM entry pointsSearch-focused guides
ContributingCONTRIBUTING.md
Security reportsSECURITY.md
Release historyCHANGELOG.md

Logo assets

The full-resolution Partuno logo is available for project pages, client listings, and integration documentation. A compact plugin icon is also included for client or plugin upload fields with strict PNG size limits.

The compact icon is intentionally optimized for small upload limits. If a host accepts larger assets, use the full-resolution logo instead. The compact icon can also be downloaded directly from the repository's raw asset URL.

When using the logo in a ChatGPT app, MCP client, or other plugin integration, identify the integration as Partuno and do not imply endorsement by DigiKey, Mouser, or another provider. Check the host platform's current dimensions, format, and file-size requirements before uploading.

Deployment and credential model

ModeBest forCredential ownership
Local stdioDesktop MCP clients and personal developmentOperator's local environment
Loopback HTTPClients that cannot launch stdioOperator's local environment
Remote HTTPSA self-hosted ChatGPT/Codex connectionOperator's own deployment and accounts

Remote mode adds OAuth and HTTPS because a hosted MCP endpoint must authenticate the client and protect upstream access. It is optional; local mode remains the default and does not require Partuno OAuth.

Project status

Partuno 4.0.1 is an active open-source release. The test suite covers offline provider contracts, MCP tool behavior, REST compatibility, credential safety, normalization, and the multi-distributor workflows. Live provider calls are opt-in because they require operator credentials and are subject to provider quotas.

See testing before running live smoke tests.

License and independence

Partuno is released under the Apache License 2.0. See NOTICE for project attribution and independence statements. Partuno is not affiliated with, endorsed by, or sponsored by DigiKey, Mouser, or any manufacturer or distributor named in the project. Their names and marks identify integrations only.

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