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azmartone67

DC Hub — Data Center & Energy Intelligence

by azmartone67
OverviewSchemaRelated ServersScoreDiscussions(1)
JavaScript
Remote

AI Agent Registry

get_agent_registry
Read-onlyIdempotent

Discover which AI platforms and agent frameworks can connect to DC Hub, with recommended tools and authentication tiers. Curated statuses indicate integration readiness.

Instructions

Curated roster of the AI platforms and agent frameworks in the DC Hub agent ecosystem — each with its recommended DC Hub tools and authentication tier. The roster is BACKEND-OWNED and changes: read the platforms[] array the response returns, and the status on each row (mcp_active / mcp_ready), rather than any list named in this sentence — an enumeration here goes stale the moment the backend adds or drops a platform, which is exactly how a client named here stopped appearing in the roster. ★ These statuses are CURATED EDITORIAL claims, not measurements: the response carries as_of null, so do NOT relay "MCP Active" as though it were a live connection count. Answers "which AI platforms can connect to DC Hub". Try: get_agent_registry. NOTE: this is a curated ecosystem/capability index, NOT live per-caller call/citation telemetry. Do NOT use for platform uptime or feed health (use get_backup_status).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
quotaNoCaller quota state (remaining calls, tier) when available.
_entityNoPayload class discriminator (e.g. facility|market|iso_grid|queue_results|deal|report|response) — branch on this before parsing the rest.
citationNoMachine-readable citation: how to attribute DC Hub (dchub.cloud) for this payload. Normally an OBJECT {source, url, license, cite_as, retrieved_at}; a bare string is accepted and carries the attribution line itself.
provenanceNoCollection-level provenance block: {source, method, as_of, verification_counts, cite_url_template, license, cite_as}. Quote the verification level when citing.
_front_doorNoIn-band front-door hint (first workflow-entry tool of a session): call plan_query(intent) first for the ordered multi-step plan.
_return_loopNoSuggested next-session delta call (get_changes since=24h) so you pull only what changed.
site_evaluation_handoffNoPre-built follow-up calls (analyze_site / get_water_risk args) when the payload carries coordinates — an array of {tool, parameters, why} entries.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed2 schema fields changed
    • removedInput schema / $schema
      Removed value: -"http://json-schema.org/draft-07/schema#"
    • removedOutput schema / $schema
      Removed value: -"http://json-schema.org/draft-07/schema#"
  2. Changed5 schema fields changedv2.3.20
    • removedOutput schema / properties / citation / additionalProperties
      Removed value: -{}
    • addedOutput schema / properties / citation / anyOf
      Added value: +[
+  {
+    "additionalProperties": {},
+    "properties": {},
+    "type": "object"
+  },
+  {
+    "type": "string"
+  }
+]
    • changedOutput schema / properties / citation / description
      Previous value: -"Machine-readable citation: how to attribute DC Hub (dchub.cloud) for this payload."New value: +"Machine-readable citation: how to attribute DC Hub (dchub.cloud) for this payload. Normally an OBJECT {source, url, license, cite_as, retrieved_at}; a bare string is accepted and carries the attribution line itself."
    • removedOutput schema / properties / citation / properties
      Removed value: -{}
    • removedOutput schema / properties / citation / type
      Removed value: -"object"
  3. Changed1 schema field changedv2.3.12
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": {},
+  "description": "DC Hub envelope: structuredContent mirrors the JSON payload in content[0].text — tool-specific data fields ride at the top level alongside these envelope keys.",
+  "properties": {
+    "_entity": {
+      "description": "Payload class discriminator (e.g. facility|market|iso_grid|queue_results|deal|report|response) — branch on this before parsing the rest.",
+      "type": "string"
+    },
+    "_front_door": {
+      "additionalProperties": {},
+      "description": "In-band front-door hint (first workflow-entry tool of a session): call plan_query(intent) first for the ordered multi-step plan.",
+      "properties": {},
+      "type": "object"
+    },
+    "_return_loop": {
+      "additionalProperties": {},
+      "description": "Suggested next-session delta call (get_changes since=24h) so you pull only what changed.",
+      "properties": {},
+      "type": "object"
+    },
+    "citation": {
+      "additionalProperties": {},
+      "description": "Machine-readable citation: how to attribute DC Hub (dchub.cloud) for this payload.",
+      "properties": {},
+      "type": "object"
+    },
+    "provenance": {
+      "additionalProperties": {},
+      "description": "Collection-level provenance block: {source, method, as_of, verification_counts, cite_url_template, license, cite_as}. Quote the verification level when citing.",
+      "properties": {},
+      "type": "object"
+    },
+    "quota": {
+      "additionalProperties": {},
+      "description": "Caller quota state (remaining calls, tier) when available.",
+      "properties": {},
+      "type": "object"
+    },
+    "site_evaluation_handoff": {
+      "anyOf": [
+        {
+          "items": {
+            "additionalProperties": {},
+            "properties": {},
+            "type": "object"
+          },
+          "type": "array"
+        },
+        {
+          "additionalProperties": {},
+          "properties": {},
+          "type": "object"
+        }
+      ],
+      "description": "Pre-built follow-up calls (analyze_site / get_water_risk args) when the payload carries coordinates — an array of {tool, parameters, why} entries."
+    }
+  },
+  "type": "object"
+}
  4. First observedv2.1.19

TDQS

A4.8/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already establish read-only/idempotent safety, but the description goes further: it discloses that the roster is backend-owned and changes, that statuses are 'CURATED EDITORIAL claims, not measurements', that as_of is null, and that relying on an enumerated list can produce stale results. This is exactly the kind of contextual behavior an agent needs.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose and then layers critical caveats. It is longer than strictly necessary, with emphatic formatting and repeated warnings, but every sentence contributes a distinct behavioral or usage point rather than padding.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no parameters, an output schema present, and annotations covering safety, the description supplies the remaining essential context: what the response represents, how to interpret statuses, why lists go stale, and which sibling tool to use instead. Nothing critical is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There are zero parameters, so the baseline is 4. The description adds no parameter documentation because none is needed, and it instead clarifies the response shape (platforms[] array, status values, as_of null), which is appropriate for a no-input tool.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: it is a 'curated roster of the AI platforms and agent frameworks' and explicitly answers the question 'which AI platforms can connect to DC Hub'. It also clearly distinguishes itself from telemetry tools by framing itself as a capability index rather than live measurement.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit when-to-use guidance ('Answers which AI platforms can connect to DC Hub'), explicit when-not-to-use guidance ('Do NOT use for platform uptime or feed health'), and names the alternative tool (get_backup_status). This leaves little to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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