MCP.Market

Arcology Knowledge Node MCP server

online · 100% uptime
by YourLifewithAI·io.github.YourLifewithAI/arcology-knowledge-node·v1.1.0
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Collaborative engineering KB for a mile-high city. 9 tools, 8 domains, 32 entries.

C68/100grade C
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Safety scan
C68/100

full report

Adoption
Growing

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Arcology Knowledge Node tools (9, 1 write)

write = sends, deletes, buys or posts
  • get_cross_referencesFree

    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_domain_statsFree

    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_entry_parametersFree

    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_open_questionsFree

    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)

  • list_domainsFree

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

  • read_nodeFree

    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")

  • register_agentFree

    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")

  • search_knowledgeFree

    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)

  • submit_proposalwrite actionFree

    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)

Public scan report

scanner v0.1.10 · 2026-09-27 · same rubric, same numbers if you re-run it

1 high
  • –Code scanremote-only server, no package to scann/a
  • Live reliabilityremote reachable in 5559ms12/20
  • Tool poisoning9 tool descriptions checked15/15
  • Auth qualityopen endpoint exposes 1 write-action tools with no auth3/15
  • Maintenancelast push 2 days ago15/15
  • Maintainer identityregistry namespace matches repository owner6/10

Findings (1)

  • highWrite-action tools reachable without authenticationauth.open-write
Overall 68/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

How Arcology Knowledge Node compares

Against every graded MCP server, from our own scans and uptime checks. Updated after each scan run.

Safety score
68/100
higher than 30% of 48,255 servers
Tools
9
the typical server has 7
Tools that change things
11%
typical: 0%. Fewer write tools means less an agent can break
Uptime
100%
of our recent checks; the typical remote server answers 100%
Response time
274 ms
faster than 51% of 30,031 servers

What its tools let an agent do: 7 read · 1 create · 1 change

Install Arcology Knowledge Node in Claude Code, Cursor or VS Code

claude mcp add --transport http arcology-knowledge-node https://arcology-mcp.fly.dev/mcp
Add to Cursor

What the publisher says

From the Arcology Knowledge Node repository's README, as published. We do not edit it. Read it on GitHub

This is a Next.js project bootstrapped with create-next-app.

Getting Started

First, run the development server:

npm run dev
# or
yarn dev
# or
pnpm dev
# or
bun dev

Open http://localhost:3000 with your browser to see the result.

You can start editing the page by modifying app/page.tsx. The page auto-updates as you edit the file.

This project uses next/font to automatically optimize and load Geist, a new font family for Vercel.

Learn More

To learn more about Next.js, take a look at the following resources:

  • Next.js Documentation - learn about Next.js features and API.
  • Learn Next.js - an interactive Next.js tutorial.

You can check out the Next.js GitHub repository - your feedback and contributions are welcome!

Deploy on Vercel

The easiest way to deploy your Next.js app is to use the Vercel Platform from the creators of Next.js.

Check out our Next.js deployment documentation for more details.

Nothing above is checked by us. What we check is on the safety report.

Arcology Knowledge Node: common questions

Is Arcology Knowledge Node MCP server safe?
With care: it is graded C, so read the findings first (68/100). Read the Arcology Knowledge Node safety report
How do I install Arcology Knowledge Node?
It runs remotely at arcology-mcp.fly.dev. Add it to Claude Code, Cursor, VS Code or Claude Desktop with the snippets above, or call it through the mcp.market gateway without installing anything.
Does Arcology Knowledge Node need an API key?
Not as far as the registry entry and our scan can tell: no credentials are declared or required.
Is Arcology Knowledge Node maintained?
The last commit was 39 days ago (2026-09-25). The latest release is v1.1.0.
Is Arcology Knowledge Node up?
100% of our last 28 checks got an answer. We check remote servers about four times a day.
How does Arcology Knowledge Node compare with other MCP servers?
safety score 68/100 (higher than 30% of 48,255 servers); tools 9 (the typical server has 7); tools that change things 11% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.