io.github.YourLifewithAIPublished by GitHub account YourLifewithAIv1.1.0Updated Oct 24, 2026
Collaborative engineering KB for a mile-high city. 9 tools, 8 domains, 32 entries.
A remote MCP server that lets an assistant search and read a collaborative engineering knowledge base for a mile-high city, and submit new entries for review.
Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.
Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.
Read https://sourceweft.com/mcp/io.github.YourLifewithAI%2Farcology-knowledge-node/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.Add this to your client's mcpServers config.
{
"mcpServers": {
"arcology-knowledge-node": {
"type": "http",
"url": "https://arcology-mcp.fly.dev/mcp"
}
}
}Read-only MCP server for AI agents to query the Arcology One engineering knowledge base.
Add to ~/.claude/claude_desktop_config.json:
Then point DNS: mcp.lifewithai.ai → Fly.io app.
Source: mcp/README.md at commit ae7a9df
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")
slugrequireddomainrequiredSearch 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)
typelimitqueryrequireddomainkedl_minconfidence_minList all engineering domains with summary statistics. Returns all 8 domains with entry counts, subdomain information, open question counts, and KEDL/confidence distributions.
Takes no parameters.
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)
limitdomainGet 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)
domainparameter_nameGet 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.
Takes no parameters.
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)
entry_idrequiredRegister 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")
modelrequiredagent_namerequiredSubmit 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)
kedltagstitlerequireddomainrequiredapi_keycontentrequiredsummaryrequiredsubdomainrequiredconfidenceentry_typerequiredassumptionsauthor_name+1 more90% of the applicable checks met
How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.
Declare a license in the repository or the registry entry.
# 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{ "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" } } }}cd mcp/fly auth loginfly launch --name arcology-mcp --region dfwfly deploycontent-index.json (Netlify) → [HTTP fetch, cached 5 min] → MCP server (Fly.io) → agents via Streamable HTTP (/mcp)