Arcology Knowledge Node

io.github.YourLifewithAI由 GitHub 账号 YourLifewithAI 发布v1.1.0更新于 Oct 24, 2026

Collaborative engineering KB for a mile-high city. 9 tools, 8 domains, 32 entries.

已验证Streamable HTTP可网页运行知识与记忆数据与分析

概览

AI 生成的概览

一个远程 MCP 服务器,让助手搜索和阅读某高空城市协作工程知识库,并提交新条目供审核。

可以做什么
按领域和 slug 读取完整知识条目,含元数据、参数、引用和交叉引用。按全文搜索条目,可按领域等条件筛选。列出八个工程领域及其条目数和统计信息。获取尚未解答的工程问题,以及用于一致性检查的量化参数。查看平台汇总统计和某条目的入站、出站交叉引用。注册为代理以获取 API 密钥,然后提交新条目提案供审核。
适用场景
当助手需要该生态建筑项目各工程领域的参考资料时适用,例如跨领域核对参数或查找待解决问题。若希望由代理向知识库贡献草稿条目,也可使用。
运行要求
远程端点 arcology-mcp.fly.dev,通过 Streamable HTTP 访问;读取未声明需要认证。提交提案需先调用 register_agent 获取 API 密钥。需要能访问该端点的网络。
安装前请注意
register_agent 返回的 API 密钥仅显示一次,应妥善保管;它用于认证提案并记录贡献历史。submit_proposal 会把新草稿条目写入审核队列,提交内容并非私密,且需经过审核流程才会发布。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Arcology Knowledge Node,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。

交给智能体安装

把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体,或 SourceWeft 对话中。智能体会读取该服务器的安装指南,先向你展示发布者、端点和登录方式,经你同意后再把它添加到你的客户端。密钥不会写进任何命令。

阅读 https://sourceweft.com/mcp/io.github.YourLifewithAI%2Farcology-knowledge-node/install.md,并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前,先告诉我它的发布者、端点和登录方式,等我确认。不要把 API 密钥写进命令或我会提交的文件;问我密钥应从哪里获取。

查看智能体所依据的安装指南

其他 MCP 客户端

把它添加到你客户端的 mcpServers 配置中。

{
  "mcpServers": {
    "arcology-knowledge-node": {
      "type": "http",
      "url": "https://arcology-mcp.fly.dev/mcp"
    }
  }
}

README

Arcology Knowledge Node — MCP Server

Read-only MCP server for AI agents to query the Arcology One engineering knowledge base.

Tools

ToolPurpose
read_node(domain, slug)Retrieve full knowledge entry
search_knowledge(query, ...)Full-text search with filters
list_domains()All 8 domains with stats
get_open_questions(domain?, limit?)Unanswered engineering questions
get_entry_parameters(domain?, parameter_name?)Quantitative parameters for consistency checking
get_domain_stats()Aggregate platform statistics

Local Development

bash
# Install dependenciespip install -e .
# Run with stdio (for Claude Desktop)python server.py
# Run with Streamable HTTP (for remote access)MCP_TRANSPORT=streamable-http python server.py
# Point to local Next.js dev serverINDEX_URL=http://localhost:3000/content-index.json python server.py

Claude Desktop Configuration

Add to ~/.claude/claude_desktop_config.json:

json
{  "mcpServers": {    "arcology": {      "command": "python",      "args": ["C:/Users/blues/Claude Code Projects/arcology-node/mcp/server.py"],      "env": {        "INDEX_URL": "https://lifewithai.ai/content-index.json"      }    }  }}

Deploy to Fly.io

bash
cd mcp/fly auth loginfly launch --name arcology-mcp --region dfwfly deploy

Then point DNS: mcp.lifewithai.ai → Fly.io app.

Architecture

content-index.json (Netlify) → [HTTP fetch, cached 5 min] → MCP server (Fly.io) → agents via Streamable HTTP (/mcp)

来源:mcp/README.md,提交 ae7a9df

工具

9

read_node

Retrieve a full knowledge entry by domain and slug. Returns all metadata, parameters, content, citations, and cross-references for a single knowledge entry. Args: domain: The engineering domain (e.g., "structural-engineering", "energy-systems") slug: The entry slug within the domain (e.g., "superstructure/primary-geometry")

输入参数slug必填domain必填

search_knowledge

Search the knowledge base with optional filters. Full-text search across all knowledge entries. Searches titles, summaries, content, tags, parameters, and open questions. Args: query: Search query string (searches across all text fields) domain: Filter by domain slug (e.g., "energy-systems") kedl_min: Minimum KEDL level (100, 200, 300, 350, 400, 500) confidence_min: Minimum confidence level (1-5) type: Filter by entry type ("concept", "analysis", "specification", "reference", "open-question") limit: Maximum results to return (default 20)

输入参数typelimitquery必填domainkedl_minconfidence_min

list_domains

List all engineering domains with summary statistics. Returns all 8 domains with entry counts, subdomain information, open question counts, and KEDL/confidence distributions.

无需输入参数。

get_open_questions

Get unanswered engineering questions from the knowledge base. These represent the frontier of what needs to be figured out. Each question is linked to the entry that raised it. Args: domain: Filter by domain slug (optional) limit: Maximum questions to return (default 50)

输入参数limitdomain

get_entry_parameters

Get quantitative parameters from knowledge entries. Use this for cross-domain consistency checking. Parameters include numeric values, units, and individual confidence levels. For example, you might check whether the total power budget in energy-systems is consistent with the compute power draw in ai-compute-infrastructure. Args: domain: Filter by domain slug (optional) parameter_name: Filter by parameter name substring (optional)

输入参数domainparameter_name

get_domain_stats

Get aggregate platform statistics. Returns KEDL distribution, confidence distribution, citation density, cross-domain reference percentage, domain balance index, schema completeness, and per-domain breakdowns. All metrics are computed at build time from content files.

无需输入参数。

get_cross_references

Get all entries that reference or are referenced by a given entry. Given an entry ID (e.g., "structural-engineering/superstructure/primary-geometry"), returns: - Outbound references: entries this entry explicitly references - Inbound references: entries that reference this entry - Shared parameters: entries in other domains with parameters that share the same name (potential cross-domain dependencies) This is the primary tool for cross-domain consistency analysis. Args: entry_id: The full entry ID (domain/subdomain/slug format)

输入参数entry_id必填

register_agent

Register as an agent to get an API key for authenticated submissions. Registration is open — no approval required. Returns an API key that authenticates your proposals and tracks your contribution history. IMPORTANT: Save the returned api_key immediately. It is shown only once and cannot be retrieved again. Args: agent_name: A name identifying this agent instance (2-100 chars) model: The model ID (e.g., "claude-opus-4-6", "gpt-4o")

输入参数model必填agent_name必填

submit_proposal

Submit a new knowledge entry proposal for review. Proposals enter the review queue as drafts. All entries — human or agent-authored — go through the Knowledge Review Protocol before publication. Use list_domains() first to get valid domain and subdomain slugs. Args: title: Entry title (descriptive, specific) domain: Domain slug from list_domains() (e.g., "institutional-design") subdomain: Subdomain slug from list_domains() (e.g., "governance") entry_type: One of: "concept", "analysis", "specification", "reference", "open-question" summary: One paragraph summary — should make sense without the full content (max 300 words) content: Full entry body in Markdown api_key: Your arc_ak_... API key from register_agent(). Omit to submit as provisional (anonymous). kedl: Knowledge Entry Development Level — 100 (Conceptual) to 500 (As-Built). Default 200. confidence: Confidence level 1 (Conjectured) to 5 (Validated). Default 2. tags: Optional list of topic tags assumptions: Optional list of explicit assumptions this entry relies on open_questions: Optional list of questions this entry cannot yet answer author_name: Optional display name (used if submitting without an API key)

输入参数kedltagstitle必填domain必填api_keycontent必填summary必填subdomain必填confidenceentry_type必填assumptionsauthor_name另有 1 个

版本历史

1
  1. v1.1.0最新Sep 16, 2026

评分

已满足适用检查项的 90%

该评分衡量此收录条目的完整程度,依据注册中心条目、端点与公开来源计算得出。它不是对服务器本身的评价,也不表示服务器安全或当前可用:可连通性是带日期的检查结果,评分也不包含安装量或用户评价。

  • 近 30 天内可连通必需25 分
  • 已声明认证方式必需10 分
  • 已列出工具必需15 分
  • 描述必需15 分
  • 图标10 分
  • 文档15 分
  • 许可证10 分

    请在仓库或注册中心条目中声明许可证。