Skip to main content
Glama
azmartone67

DC Hub — Data Center & Energy Intelligence

Predict Market Trajectory

predict_market_trajectory
Read-onlyIdempotent

Forecast a market's power and constraint scores for next 1-8 quarters, with widening confidence bands. See whether the metro is trending toward BUILD or AVOID.

Instructions

Forecast a DCPI market's near-term trajectory (next 1-8 quarters). Projects excess_power_score and constraint_score forward with confidence bands that WIDEN with horizon, from DC Hub's daily DCPI snapshot history — the only source that can, because it owns the time-series. Use to answer "is this market trending toward BUILD or AVOID?" or "will Dallas power stay tight over the next 6 months?". Params: market_slug (required, metro slug e.g. dallas, phoenix, northern-virginia — valid slugs come from rank_markets / get_market_dcpi_rank); horizon_quarters (optional 1-8, default 4; 2 = ~6 months out). Returns {market_slug, method, basis{history_points, history_span_days, slope_per_day, trend}, horizon_quarters, projection[{quarter_out, excess_power_score, excess_power_band, constraint_score, constraint_band}], caveat, snapshot_record}. HONEST: linear trend extrapolation, NOT a guarantee — bands widen with horizon and short history; needs >=3 daily snapshots or it declines. Do NOT use for a single point-in-time verdict (use get_market_dcpi_rank) or to rank many markets (use rank_markets).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
market_slugYesMarket slug (metro), e.g. dallas, phoenix, northern-virginia — valid slugs come from rank_markets / get_market_dcpi_rank
horizon_quartersNoForecast horizon in quarters (1-8, default 4); 2 = ~6 months ahead

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. Changed3 schema fields changed
    • removedInput schema / $schema
      Removed value: -"http://json-schema.org/draft-07/schema#"
    • addedInput schema / required
      Added value: +[
      +  "market_slug"
      +]
    • 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. Addedv2.3.7

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is known. The description adds substantial behavioral context: linear trend extrapolation, confidence bands widening with horizon, minimum 3 daily snapshots requirement, and the data source (DC Hub daily snapshot history). It honestly discloses that the forecast is 'NOT a guarantee.' No contradiction with annotations.

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

Conciseness5/5

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

Although long, every sentence carries functional weight: purpose, when-to-use, parameter breakdown, return shape, honesty/caveat, and exclusions. The core purpose is front-loaded and the structure is logical, moving from high-level capability to specific constraints.

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?

Given the tool's moderate complexity (2 params, output schema), the description covers purpose, prerequisites (valid slugs and minimum snapshot history), parameter semantics, return structure, limitations, and alternative routing. Nothing an agent needs to correctly invoke or interpret this forecast tool is missing.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema fully documents both parameters. The description repeats the same parameter information (valid slugs source, horizon range/default) without adding new meaning beyond the schema. Per the baseline for high-coverage schemas, this is a 3.

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?

Description opens with a specific verb and resource: 'Forecast a DCPI market's near-term trajectory (next 1-8 quarters)' and names the projected metrics (excess_power_score, constraint_score). It also differentiates from siblings by explicitly stating it is not for point-in-time verdicts (use get_market_dcpi_rank) or market ranking (use rank_markets).

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?

Includes explicit when-to-use examples ('is this market trending toward BUILD or AVOID?', 'will Dallas power stay tight...') and clear when-not-to-use guidance with named alternatives. This is the strongest possible guidance: it tells the agent both the conditions and the sibling tools to choose instead.

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

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/azmartone67/dchub-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server