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Glama

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

by cloud.dchub

Deal Autopsy

deal_autopsy
Read-onlyIdempotent

Tracked data-center M&A / capex deal flow with the DCPI grid-reality verdict overlaid on each deal market — "what is the real play?". Returns recent deals (buyer, seller, value, market) + each market DCPI verdict and time-to-power; with a paid key, the per-deal autopsy read (long-dated land/power option vs near-term build vs queue gamble). Progressive disclosure to keep the default cheap: by default each read ships only a comparables COUNT (the verdict text is always included); pass comparables="summary" for the top-2 grounding signals, or comparables="full" to expand the complete cited set for a deal you're drilling into. Answers "who is actually buying data centers right now, and are those markets any good", "what is the real play behind this deal". Try: deal_autopsy limit=15.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoNumber of recent deals to return (default ~15)
comparablesNoComparables detail: "none" (default — count only, cheapest), "summary" (top-2 grounding signals), or "full" (the complete cited set). Escalate only for deals you're drilling into.

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

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, iempotentHint, and destructiveHInt false, so the safety profile is covered. The description adds meaningful behavioral context beyond annotations: paid-key gating for full autopsy reads, default cheap progressive disclosure, and the comparables escalation path from count to summary to full. 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.

Conciseness4/5

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

The description is information-dense and front-loaded with the core purpose, then moves to return contents, paid-key behavior, and comparables escalation. It earns its space, though the 'real play' phrasing appears twice and could be tightened slightly.

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?

For a tool with two optional params and an output schema, the description covers purpose, output shape, auth-dependent behavior, default vs escalated parameter choices, and an example. Nothing essential for correct invocation 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?

Input schema coverage is 100%, so the baseline is 3. The description adds value by framing comparables as an escalation for drilling into a deal, explaining the default 'count only' behavior, and giving a direct example invocation with limit=15. This goes slightly beyond the schema descriptions.

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?

States specifically that the tool returns data-center M&A/capex deal flow with DCPI verdicts overlaid on each market, and positions it around the question 'what is the real play?'. This is a clear verb+resource description that distinguishes it from siblings like list_transactions or get_market_dcpi_rank.

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

Usage Guidelines4/5

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

Gives concrete selection context: it answers 'who is actually buying data centers right now' and 'what is the real play behind this deal', plus a 'Try: limit=15' example. It does not explicitly name alternatives or when-not-to-use conditions, but the use cases are clear enough.

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