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。
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Semahash

作者:emergent-wisdom版本 0.10.0i★ –i在你的电脑上运行
注册名称io.github.emergent-wisdom/semahash

安装

概览

作者提供的说明(英文原文)

Content-addressed semantics: fail-closed handshakes over 617 cognitive patterns.

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: 其他

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)。
  • 注册中心没有列出需要填写的密钥。

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": {
    "semahash": {
      "command": "uvx",
      "args": [
        "semahash",
        "mcp"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add semahash -- uvx semahash mcp

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": {
    "semahash": {
      "command": "uvx",
      "args": [
        "semahash",
        "mcp"
      ]
    }
  }
}

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": {
    "semahash": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "semahash",
        "mcp"
      ]
    }
  }
}

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。

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 emergent-wisdom 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“其他”中的其他服务器比较i

  • 星标数多于此分类中其他 32718 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 32718 个服务器的 59% 更新
  • 基础检查结果等于或优于此分类中其他 32718 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

Semahash 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?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

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(0.10.0)于27天前进入注册中心。

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:Spec Driven Development, Remote Desktop Commander, MemberVault MCP by usefulapi

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

Spec Driven Development

作者:formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

在你的电脑上运行★ 440MIT14个月前更新
安装

Remote Desktop Commander

作者:desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

在云端运行★ 211前天更新
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。

Sema: When the Hash Is the Word

Content-addressed semantics for multi-agent coordination.

Sema is a content-addressed reference system for reasoning and communication. Participants encode and hash information under an agreed representation, then reuse the content address as a verifiable reference, optionally paired with a human-readable handle. Matching full references establishes identity of the resolved hashed content; semantic equivalence, correctness, and enforcement remain separate questions.

Web: semahash.org · Discord: Join

Install

MCP Server (recommended)

Add to any MCP client (Claude Code, Cursor, VS Code, Windsurf, Claude Desktop):

{

"mcpServers": { "sema": { "command": "uvx", "args": ["--from", "semahash[mcp]", "sema", "mcp"] } } }

Or via Claude Code CLI:

claude mcp add sema -- uvx --from "semahash[mcp]" sema mcp

This uses uv to download, install, and run sema in an isolated environment on first invocation, then caches it for subsequent calls.

Claude Code plugin (MCP server + skill)

Sema also ships as a Claude Code plugin — MCP server plus a skill that teaches the agent the search/resolve/mint/handshake workflow:

# One-time: add the Emergent Wisdom marketplace

claude plugin marketplace add emergent-wisdom/marketplace

Install the plugin

claude plugin install sema

This gives you the MCP server and the sema-usage skill (auto-loaded), which teaches when to search vs mint, how to embed handles in text, and how to verify meaning at boundaries. The skill is a Claude Code convenience — the MCP server works with any client.

For local development:

claude --plugin-dir /path/to/sema
Permanent install (pip)
pip install "semahash[mcp]"

For CLI-only use (no MCP server):

pip install semahash

Quick Start

Use with AI Agents (MCP)

Already covered above via the JSON config or pip install path. For development against this repo:

git clone https://github.com/emergent-wisdom/sema.git

pip install -e "./sema[mcp]"

Your agent now has access to sema_search, sema_lookup, sema_handshake, and 9 more tools. Any MCP-compatible client works — Sema exposes a standard stdio server.

Verify it works — ask your agent: *"Search sema for coordination patterns and handshake on StateLock"*

Sema exposes a standard MCP stdio server — any MCP-compatible client works, including OpenClaw (openclaw mcp set sema '{"command":"uvx","args":["--from","semahash[mcp]","sema","mcp"]}').

Use via CLI
# Search the vocabulary

sema search "coordination"

Look up a specific pattern

sema resolve StateLock

Print a pattern's full definition

sema show StateLock

Browse the graph structure

sema skeleton

Watch the active vocabulary in the local view (binds to 127.0.0.1 by default)

sema serve --open

Bring Your Own Vocabulary

Build a private registry from scratch — no PR or maintainer in the loop:

sema init ./mylib.db

sema use ./mylib.db sema apply --add path/to/MyPattern.json sema search "..."

Subsequent sema commands (including sema mcp) read from your private registry. (SEMA_DB_PATH, if set, overrides sema use.) See CONTRIBUTING.md for the canonical contribution path and docs/specification/versioning.md for the refinement and supersession policy.

Package a project database as a verified, standalone library release:

sema package ./mylib.db \

--name mylib \ --version 1.0.0 \ --output-dir dist/mylib-1.0.0 \ --github-repo acme/sema-mylib

Publish the generated library.json and versioned ZIP as assets on the corresponding published GitHub Release. Consumers install the Release asset URL for library.json—not the repository URL or a branch:

sema install https://github.com/acme/sema-mylib/releases/latest/download/library.json

sema use mylib sema list sema root

It installs one verified snapshot at a time rather than merging vocabularies; the bundled vocabulary remains the offline default. Use sema update mylib to follow the installed library's recorded release pointer. See Publishing and Installing Vocabulary Libraries for the complete DeFi authoring, dependency-closure, packaging, GitHub Release, and update workflow.

Libraries published on semahash.org can be found and installed by name, without an account:

sema registry search defi

sema install mylib

To list a release there so other people and agents can find it, log in once and publish from the command line:

sema login        # approve the short code in your browser, once

sema registry import https://github.com/acme/sema-mylib/releases/latest/download/library.json

An agent can log in with a key that you create on your semahash.org profile page instead: it pipes the key to sema login --key - or calls the sema_library_login MCP tool.

The login follows the OAuth 2.0 device authorization flow, so it also works from an agent or a machine without a browser. To use another deployment, run sema login --registry https://registry.example. A successful login remembers that registry for subsequent commands. --registry and SEMA_REGISTRY_URL override the remembered choice; https://semahash.org is the first-use default.

Use in Python
from sema.core.registry import RegistryManager

registry = RegistryManager() pattern = registry.get_pattern("StateLock")

Look up the canonical reference

print(pattern["sema_ref"]) # StateLock#c9c2

Verify an inline reference before relying on it

assert pattern["sema_ref"] == "StateLock#c9c2"

Try the Protocol (No API Keys Needed)
python experiments/demos/local_handshake.py

See the handshake in action: matching hashes PROCEED, mismatched hashes HALT, and unknown patterns HALT. Cooperative mode accepts short prefixes for drift detection; strict mode requires the full hash. Takes 2 seconds.

How It Works

word = hash(canonical(definition))

Take any concept (a coordination protocol, a reasoning pattern, a trust mechanism), express it in canonical form, hash it. That hash IS the word. Change one byte in the definition, get a different word.

Cooperative: sema_handshake("StateLock#c9c2")

-> PROCEED with assurance="prefix", or HALT

Strict: sema_handshake("StateLock", " ", strict=true) -> PROCEED with assurance="full_hash", or HALT

This is the Anti-Postel principle: strict mode proceeds only on full-hash identity; cooperative mode uses compact prefixes as a non-adversarial drift signal. Mismatches fail closed in both modes.

The Vocabulary

The bundled vocabulary spans 4 layers:

  • Physics — Immutable substrate (locks, entropy, causality)
  • Mind — Hybrid cognition (reasoning, inference, strategy)
  • Society — Multi-agent coordination (economics, governance, protocols)
  • Infrastructure — Operational constraints (data structures, verification)

Each pattern is a content-addressed behavioral definition. Concrete cards may add machine-verifiable contracts, invariants, failure modes, parameters, and typed dependencies where those fields are identity-defining.

MCP Tools

When running as an MCP server (sema mcp), these tools are available:

ToolDescription
sema_searchSearch patterns by name, description, or meaning
sema_lookupGet a pattern by its reference (e.g., StateLock#c9c2)
sema_resolveGet a pattern with dependencies expanded
sema_handshakeFail-closed semantic verification between agents
sema_mintCreate a new pattern (validate, hash, add to vocabulary)
sema_propose_contextCompute a context digest for a multi-agent definition set (drift detection)
sema_verify_contextVerify a context proposal from another agent
sema_treeBrowse vocabulary by layer and category
sema_validateValidate a pattern JSON for correctness
sema_statsVocabulary statistics
sema_graph_skeletonUltra-minimal graph overview (~150 tokens)
sema_reset_sessionClear session cache so searches return full results again
sema_library_searchFind libraries published on semahash.org
sema_library_installVerify and install a library by name or library.json URL
sema_library_loginStore a semahash.org key that the user gives the agent
sema_library_publishPublish a GitHub release on semahash.org, after the user agrees

Local View

pip install "semahash[api]"

sema serve --open

Opens http://localhost:3000

The local view shows the vocabulary selected with sema use, the same one a connected agent writes to. It follows later switches, and its 3D graph grows while the agent mints: new patterns light up and appear in a live list. The pattern browser has card, list, and JSON views. Development stays on your computer; semahash.org hosts finished libraries, and a writable vocabulary's page lists the optional steps to publish one there.

Experiments

The experiments/ directory contains reproducible evaluations of Sema's claims and implementation boundaries.

Delta reconstruction

The public v0.3.0 to v0.4.0 reconstruction experiment checks whether the current graph and hash-cascade algorithm can rebuild a target vocabulary from an earlier release. It compares both aggregate roots, semantic pattern content, the logical dependency graph, unhashed metadata, and the complete normalized read model rather than treating root equality as complete release equality. It also demonstrates the safe reconstruction path: integrate the delta into a complete staged card snapshot, compile a fresh database, verify the result, and only then activate it.

.venv/bin/python experiments/delta_reconstruction/reproduce.py

The experiment and its expected results are documented in experiments/delta_reconstruction/README.md. Small synthetic versions of its addition, removal, rename, cascade, metadata, and failure cases run in the regular test suite.

Multi-agent design challenge

The controlled multi-agent design challenge compares three conditions:

ConditionSemaTurnsOutcome
A: Natural language onlyNo4Design rejected
B: Sema vocabularyYes11SAD Engine approved
C: Sema + protocolYes25SAD Engine with exhaustive vetting

Agents with Sema patterns produced physics-grounded designs that survived adversarial scrutiny. Agents without Sema produced shallow designs that failed safety review.

To reproduce:

`bas

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