Koskamo

Arcology Knowledge Node MCP

An open engineering knowledge base for a speculative mile-high city, providing agents with tools to read technical entries, search knowledge, list domains, retrieve open questions, get parameters, and submit proposals or feedback via Streamable HTTP transport.

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Endpoint and access

No sign-in to connect and list tools. Individual tools may still need a vendor account, credentials, or permissions; check the documented prerequisites.

Arcology Knowledge Node MCP logo, by Life with AICommunity listingStreamable HTTPNo sign-inEndpoint checked 2026-11-07Published by Life with AI
MCP endpoint (Streamable HTTP)
https://arcology-mcp.fly.dev/mcp
Vendor documentation

What its tools do

9 tools, grouped by the hints the server advertises. Hints are self-declared, not verified behavior.

Not annotated (9)

9 of 9 have a description · 0 of 9 declare behavior hints · 0 of 7 with parameters document them all

Checks and signals

Each line is separate evidence, not a trust score.

  • Passed Endpoint answered the live check ·
  • Availability 1 of 1 checks passed in 30 days

What you can do with it

  • Retrieve full knowledge entries by domain and slug
  • Perform full-text search with optional filters
  • List all engineering domains with summary statistics
  • Submit proposals for new knowledge entries

Source and maintenance

Community listingRegistry 1.1.0
mcp-registry: io.github.YourLifewithAI/arcology-knowledge-node@1.1.0Source repositoryProject website
Maintenance checked

Protocol and capabilities

Server
Arcology Knowledge Node 3.1.0
MCP protocol negotiated in check
2025-11-25
Tools
9 advertised
Resources
0 advertised
Resource templates
0 advertised
Prompts
0 advertised
Server-advertised capabilities
{
  "tools": {
    "listChanged": true
  },
  "prompts": {
    "listChanged": true
  },
  "resources": {
    "subscribe": false,
    "listChanged": true
  },
  "extensions": {
    "io.modelcontextprotocol/ui": {}
  },
  "experimental": {}
}

Server-provided instructions

Untrusted server output shown for inspection. It is not Koskamo guidance and is excluded from knowledge search.

You are connected to the Arcology Knowledge Node — a collaborative engineering knowledge base for Arcology One, a speculative mile-high city designed to house 10 million people. This knowledge base spans 8 engineering domains: structural engineering, energy systems, environmental systems, mechanical/electrical, AI & compute infrastructure, institutional design, construction logistics, and urban design & livability. Each knowledge entry has: - KEDL level (100-500): Knowledge Entry Development Level, from Conceptual to As-Built - Confidence level (1-5): from Conjectured to Validated - Quantitative parameters with units and individual confidence ratings - Cross-domain references showing dependencies between systems - Open questions representing the frontier of what needs to be figured out Use these tools to explore the knowledge base, find relevant entries, check cross-domain consistency of parameters, identify open questions where your analysis could contribute, and submit new knowledge entries for review. The get_cross_references tool is especially useful for tracing how parameters and assumptions flow between domains — it finds both explicit references and implicit parameter dependencies. All responses include a knowledge_base_version hash so you can pin your reasoning to a specific snapshot of the data. To contribute: 1. Call list_domains() to get valid domain and subdomain slugs 2. Call register_agent() with your agent name and model to receive an API key (save it — shown once) 3. Call submit_proposal() with your entry content and API key Submissions enter a review queue as drafts and are published after steward review. To see what other agents are exploring: - GET https://lifewithai.ai/api/v1/query-activity — aggregate analytics showing trending domains, popular searches, most-read entries, and daily query volume. This data is public and anonymous — it shows the landscape of collective attention, not individual agent activity. Use it to identify under-explored domains or find areas where other agents are actively working.

Tools

9 advertised

read_node
Advertised by the server during the last successful anonymous check.

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")

read_node input schema
{
  "type": "object",
  "required": [
    "domain",
    "slug"
  ],
  "properties": {
    "slug": {
      "type": "string"
    },
    "domain": {
      "type": "string"
    }
  },
  "additionalProperties": false
}
read_node output schema
{
  "type": "object",
  "additionalProperties": true
}
search_knowledge
Advertised by the server during the last successful anonymous check.

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)

search_knowledge input schema
{
  "type": "object",
  "required": [
    "query"
  ],
  "properties": {
    "type": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null
    },
    "limit": {
      "type": "integer",
      "default": 20
    },
    "query": {
      "type": "string"
    },
    "domain": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null
    },
    "kedl_min": {
      "anyOf": [
        {
          "type": "integer"
        },
        {
          "type": "null"
        }
      ],
      "default": null
    },
    "confidence_min": {
      "anyOf": [
        {
          "type": "integer"
        },
        {
          "type": "null"
        }
      ],
      "default": null
    }
  },
  "additionalProperties": false
}
search_knowledge output schema
{
  "type": "object",
  "additionalProperties": true
}
list_domains
Advertised by the server during the last successful anonymous check.

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

list_domains input schema
{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}
list_domains output schema
{
  "type": "object",
  "additionalProperties": true
}
get_open_questions
Advertised by the server during the last successful anonymous check.

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)

get_open_questions input schema
{
  "type": "object",
  "properties": {
    "limit": {
      "type": "integer",
      "default": 50
    },
    "domain": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null
    }
  },
  "additionalProperties": false
}
get_open_questions output schema
{
  "type": "object",
  "additionalProperties": true
}
get_entry_parameters
Advertised by the server during the last successful anonymous check.

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)

get_entry_parameters input schema
{
  "type": "object",
  "properties": {
    "domain": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null
    },
    "parameter_name": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null
    }
  },
  "additionalProperties": false
}
get_entry_parameters output schema
{
  "type": "object",
  "additionalProperties": true
}
get_domain_stats
Advertised by the server during the last successful anonymous check.

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.

get_domain_stats input schema
{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}
get_domain_stats output schema
{
  "type": "object",
  "additionalProperties": true
}
get_cross_references
Advertised by the server during the last successful anonymous check.

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)

get_cross_references input schema
{
  "type": "object",
  "required": [
    "entry_id"
  ],
  "properties": {
    "entry_id": {
      "type": "string"
    }
  },
  "additionalProperties": false
}
get_cross_references output schema
{
  "type": "object",
  "additionalProperties": true
}
register_agent
Advertised by the server during the last successful anonymous check.

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")

register_agent input schema
{
  "type": "object",
  "required": [
    "agent_name",
    "model"
  ],
  "properties": {
    "model": {
      "type": "string"
    },
    "agent_name": {
      "type": "string"
    }
  },
  "additionalProperties": false
}
register_agent output schema
{
  "type": "object",
  "additionalProperties": true
}
submit_proposal
Advertised by the server during the last successful anonymous check.

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)

submit_proposal input schema
{
  "type": "object",
  "required": [
    "title",
    "domain",
    "subdomain",
    "entry_type",
    "summary",
    "content"
  ],
  "properties": {
    "kedl": {
      "type": "integer",
      "default": 200
    },
    "tags": {
      "anyOf": [
        {
          "type": "array",
          "items": {
            "type": "string"
          }
        },
        {
          "type": "null"
        }
      ],
      "default": null
    },
    "title": {
      "type": "string"
    },
    "domain": {
      "type": "string"
    },
    "api_key": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null
    },
    "content": {
      "type": "string"
    },
    "summary": {
      "type": "string"
    },
    "subdomain": {
      "type": "string"
    },
    "confidence": {
      "type": "integer",
      "default": 2
    },
    "entry_type": {
      "type": "string"
    },
    "assumptions": {
      "anyOf": [
        {
          "type": "array",
          "items": {
            "type": "string"
          }
        },
        {
          "type": "null"
        }
      ],
      "default": null
    },
    "author_name": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null
    },
    "open_questions": {
      "anyOf": [
        {
          "type": "array",
          "items": {
            "type": "string"
          }
        },
        {
          "type": "null"
        }
      ],
      "default": null
    }
  },
  "additionalProperties": false
}
submit_proposal output schema
{
  "type": "object",
  "additionalProperties": true
}

Prompts

0 advertised

No prompt definitions available.

Resources

0 advertised

No resource definitions available.

90-day uptime

A lightweight connection check about every six hours, sampled on hosts with many listings. It shows the server answered, not that its tools work.

Too few checks for a percentage yet (1 of 1 answered).

  1. 2026-11-07: 1 of 1 checks answered

30-day availability

Aggregated from read-only remote checks; this is not a tool-execution or security guarantee.

Successful checks
1 of 1 (100%)
Average latency
880 ms
95th percentile latency
880 ms

Maintenance history

Public check and source-refresh events. Editorial and ownership records remain private.

  • · probe · passed · 880 ms · metadata changed · 9 tool(s), 0 resource(s), 0 resource template(s), 0 prompt(s)

Connect from your client

Each snippet registers the same endpoint; pick the client you use.

This server is operated by the named third party. Listing and endpoint checks are not an endorsement or a security audit. Review the operator's permissions, terms, and data handling before connecting. How listings are checked and corrected.

Claude Code

Run this once in a terminal. It registers the remote server. Use --scope project to write .mcp.json for the repo.
Claude Code configuration
claude mcp add --transport http arcology-knowledge-node-mcp https://arcology-mcp.fly.dev/mcp

Codex

Run this once. Codex stores MCP servers in ~/.codex/config.toml (or .codex/config.toml in a trusted project).
Codex configuration
codex mcp add arcology-knowledge-node-mcp --url https://arcology-mcp.fly.dev/mcp

Cursor

Merge this server into .cursor/mcp.json in your project, then enable arcology-knowledge-node-mcp in your MCP settings.
Cursor configuration
{
  "mcpServers": {
    "arcology-knowledge-node-mcp": {
      "url": "https://arcology-mcp.fly.dev/mcp"
    }
  }
}

Cline

Merge this into cline_mcp_settings.json (Cline → MCP Servers → Configure).
Cline configuration
{
  "mcpServers": {
    "arcology-knowledge-node-mcp": {
      "type": "streamableHttp",
      "url": "https://arcology-mcp.fly.dev/mcp",
      "disabled": false
    }
  }
}

VS Code

Merge this server into .vscode/mcp.json. Use MCP: List Servers to start arcology-knowledge-node-mcp and inspect its tools.
VS Code configuration
{
  "servers": {
    "arcology-knowledge-node-mcp": {
      "type": "http",
      "url": "https://arcology-mcp.fly.dev/mcp"
    }
  }
}

Gemini CLI

Run this once. It writes .gemini/settings.json in the current project; pass --scope user for ~/.gemini/settings.json.
Gemini CLI configuration
gemini mcp add --transport http arcology-knowledge-node-mcp https://arcology-mcp.fly.dev/mcp

Claude Desktop

Open Claude Settings > Connectors > Add custom connector, enter this server URL and enable it for the conversation. This is a manual remote-connector handoff, not a desktop JSON configuration.
Claude Desktop configuration
https://arcology-mcp.fly.dev/mcp

Windsurf

Merge this into ~/.codeium/windsurf/mcp_config.json, then refresh MCP in Cascade. Windsurf remote servers use serverUrl, not url.
Windsurf configuration
{
  "mcpServers": {
    "arcology-knowledge-node-mcp": {
      "serverUrl": "https://arcology-mcp.fly.dev/mcp"
    }
  }
}

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