此 MCP 可以做什么
Searches and retrieves a collaborative engineering knowledge base with cross-references, quantitative parameters, citations, open questions, and proposal submission.
功能
工具
9
工具
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)
输入模式
{'type': 'object', 'required': ['entry_id'], 'properties': {'entry_id': {'type': 'string'}}, 'additionalProperties': False}
输出模式
{'type': 'object', 'additionalProperties': True}
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.
输入模式
{'type': 'object', 'properties': {}, 'additionalProperties': False}
输出模式
{'type': 'object', 'additionalProperties': True}
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)
输入模式
{'type': 'object', 'properties': {'domain': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'default': None}, 'parameter_name': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'default': None}}, 'additionalProperties': False}
输出模式
{'type': 'object', 'additionalProperties': True}
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)
输入模式
{'type': 'object', 'properties': {'limit': {'type': 'integer', 'default': 50}, 'domain': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'default': None}}, 'additionalProperties': False}
输出模式
{'type': 'object', 'additionalProperties': True}
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.
输入模式
{'type': 'object', 'properties': {}, 'additionalProperties': False}
输出模式
{'type': 'object', 'additionalProperties': True}
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")
输入模式
{'type': 'object', 'required': ['domain', 'slug'], 'properties': {'slug': {'type': 'string'}, 'domain': {'type': 'string'}}, 'additionalProperties': False}
输出模式
{'type': 'object', 'additionalProperties': True}
register_agent
Register as an agent to get an API key for authenticated submissions.
Registration is open â 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")
输入模式
{'type': 'object', 'required': ['agent_name', 'model'], 'properties': {'model': {'type': 'string'}, 'agent_name': {'type': 'string'}}, 'additionalProperties': False}
输出模式
{'type': 'object', 'additionalProperties': True}
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)
输入模式
{'type': 'object', 'required': ['query'], 'properties': {'type': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'default': None}, 'limit': {'type': 'integer', 'default': 20}, 'query': {'type': 'string'}, 'domain': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'default': None}, 'kedl_min': {'anyOf': [{'type': 'integer'}, {'type': 'null'}], 'default': None}, 'confidence_min': {'anyOf': [{'type': 'integer'}, {'type': 'null'}], 'default': None}}, 'additionalProperties': False}
输出模式
{'type': 'object', 'additionalProperties': True}
submit_proposal
Submit a new knowledge entry proposal for review.
Proposals enter the review queue as drafts. All entries â human or
agent-authored â 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 â 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 â 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)
输入模式
{'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': None}, 'title': {'type': 'string'}, 'domain': {'type': 'string'}, 'api_key': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'default': None}, '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': None}, 'author_name': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'default': None}, 'open_questions': {'anyOf': [{'type': 'array', 'items': {'type': 'string'}}, {'type': 'null'}], 'default': None}}, 'additionalProperties': False}
输出模式
{'type': 'object', 'additionalProperties': True}
历史
近期工具变更
已添加
submit_proposal
2026年9月17日 12:53
已添加
register_agent
2026年9月17日 12:53
已添加
get_cross_references
2026年9月17日 12:53
已添加
get_domain_stats
2026年9月17日 12:53
已添加
get_entry_parameters
2026年9月17日 12:53
已添加
get_open_questions
2026年9月17日 12:53
已添加
list_domains
2026年9月17日 12:53
已添加
search_knowledge
2026年9月17日 12:53
已添加
read_node
2026年9月17日 12:53
发现
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