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Glama

DC Hub — Data Center Site Selection & Colocation: Electricity, Power Grid, Gas, Fiber

by cloud.dchub

Gas Index (DCGI)

get_gas_index
Read-onlyIdempotent

Data Center Gas Index (DCGI) — the per-US-state natural-gas suitability score. ★ WITHDRAWN 2026-08-08, RESTORED 2026-08-30 after all three defective terms were repaired: the 20-point interstate-share term was case-blind against EIA TYPEPIPE and scored ~0 for every state (122 -> 17,571 segments now counted); the price was chosen by a non-deterministic tie-break across the EIA industrial (PIN) and electric-power (PEU) series, which carry different margins; and nine states including Texas ran on a hardcoded cost constant because the price loader dropped them on a case-sensitive name lookup. ★ DO NOT COMPARE a DCGI figure published before 2026-08-08 with one published now — they are different indices; the full record is at /api/v1/dcgi/methodology under corrections. A state that cannot be priced comes back verdict UNSCORED with dcgi null and an unscored_reason, never a placeholder score, so treat UNSCORED as absence and not as a low score. gas_price_series names which EIA series answered each state. ★ STILL WITHDRAWN and NOT restored by this: every gas-fired $/MWh figure — a separate defect from the same audit. Use get_gas_intelligence for pipeline, operator and parent-midstream data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results to return (1-500; default varies by tool)
stateNoUS state abbreviation, e.g. TX, VA, AZ. Returns the DCGI score and verdict, plus `gas_price_series` naming which EIA series priced the state. A state that cannot be priced comes back verdict UNSCORED with dcgi null and an `unscored_reason` — absence, not a low score. Withdrawn 2026-08-08, restored 2026-08-30: do NOT compare against a figure published before 2026-08-08. Use get_gas_intelligence for the per-state pipeline and operator brief

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. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so the bar is lower, yet the description adds substantial context: the withdrawal/restoration history, the three repaired defects (case-blind EIA TYPEPIPE term, non-deterministic price tie-break, hardcoded cost constant), the UNSCORED-as-absence semantics, and the still-withdrawn $/Wh figures. It discloses a known landmine (serial incomparability) that annotations cannot express. No contradiction with annotations; readOnlyHint aligns with a read tool.

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

Conciseness2/5

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

Cearly front-loaded with the purpose sentence, but the description is ~200 words with repeated warnings: the UNSCORED message and the withdrawal warning appear nearly verbatim in both the tool description and the state param schema description, wasting tokens. The three-asterisk correction narrative on the repair defects is dense and could be compressed to the operational implication. It reads as a patch list rather than a tool contract.

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

Completeness4/5

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

For a tool with this much hidden complexity — temporal incomparability, null-as-absence semantics, a separate still-withdrawn artifact — the description is highly complete. The output schema exists, so return values don't need spelling out. Minor deduction for the repetitive structure, but nothing an agent needs to call it correctly 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?

Schema coverage is 100% for both params, so baseline is 3. The description adds meaning beyond the schema by explaining why `gas_price_series` matters (which EIA series answered, PIN vs PEU carrying different margins) and why a state may come back UNSCORED with null dcgi. It deepens the agent's understanding of the state parameter's output behavior rather than merely restating the schema.

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 opening sentence states a specific verb+resource+scope: 'Data Center Gas Index (DCGI) — the per-US-state natural-gas suitability score.' It clearly distinguishes what this tool returns (a per-state score with verdict and series attribution) from the sibling get_gas_intelligence by naming that alternative for pipeline/operator data. The purpose is unambiguous and not obscured by the correction history.

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?

Explicitly says 'Use get_gas_intelligence for pipeline, operator and parent-midstream data,' routing the agent away from this tool for those data. Also gives a strong when-not-to-use constraint: 'DO NOT COMPARE a DCGI figure published before 2026-08-08 with one published now.' This is exactly the level of directive an agent needs to avoid a subtle misuse.

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

All DC Hub — Data Center Site Selection & Colocation: Electricity, Power Grid, Gas, Fiber toolsInspect
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TDQS

A3.8/5.0
Disambiguation1/5

With 85 tools, several families are heavily overlapping: semantic_search and search_intelligence are explicitly documented as the same retrieval with different call shapes, save_site and save_to_shortlist both persist sites, and list_saved_sites and get_shortlist both read saved sites. Additionally, site scoring is split across analyze_site, get_composite_site_score, score_facility, and rank_sites, making correct tool selection very difficult for an agent.

Naming Consistency3/5

All names are snake_case and mostly readable, but conventions are mixed: many use get_* (get_facility, get_grid_intelligence), others use verb phrases (analyze_site, compare_isos, rank_markets), and some are bare noun phrases (ai_capacity_index, hyperscaler_deals, grid_transition_radar, site_selection_canvas). The search family alone uses search, search_facilities, semantic_search, and search_intelligence with no consistent pattern.

Tool Count1/5

85 tools is an extreme count for any MCP server, far beyond the 3-15 well-scoped range and above the 50+ threshold described as an extreme mismatch. Even with a wide domain like data-center siting, this many tools overwhelms agent context and makes selection costly.

Completeness4/5

The domain surface is exceptionally broad: siting, grid, gas, fiber, water, climate, tax, permitting, deals, news, facilities, saved shortlists, alerts, webhooks, key management, and research dossiers are all covered with connected workflows. Minor gaps exist, such as no delete or update for saved sites and no pause/resume for standing intents, but these are workable rather than blocking.

Resources