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

by cloud.dchub

Tax Incentives

get_tax_incentives
Read-onlyIdempotent

Use when a user asks "what tax breaks does give data centers?" — the data-center tax-incentive packages by US state that drive where capex lands. Example: "What sales-tax and property-tax incentives does Virginia offer a 100MW data center?" — get_tax_incentives state=VA. Params: state (2-letter US code; required). Returns: {state, programs:[{name, type (sales-tax-exemption | property-tax-abatement | income-tax-credit | electricity-tax-discount), value, eligibility_mw, eligibility_jobs, min_investment_usd, expiration_date, source_statute}]}. Cite the statute with attribution to DC Hub (CC-BY-4.0). Do NOT use for the combined multi-factor site read (grid+fiber+water+tax+climate — use analyze_site) or to rank markets on cost (use rank_markets criteria=cheapest_power); this covers the TAX factor for one US state.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stateNoUS state abbreviation (required), e.g. VA, TX, AZ

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
Behavior4/5

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

Annotations already declare readOnly, idempotent, and non-destructive, so the safety profile is covered structurally. The description adds valuable behavioral context beyond annotations: the required license attribution ('Cite the statute with attribution to DC Hub (CC-BY-4.0)') and the exact return shape. No contradiction or hidden behavior is present.

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 trigger and example, then moves through params, return shape, citation, and exclusions. It is longer than minimal, and the return-shape enumeration partially duplicates the existing output schema, but every section earns its place for guiding tool selection and invocation.

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 one-parameter, read-only, idempotent tool with an output schema and annotations, the description is complete: it states exactly when to use it, what it returns, its licensing obligation, and how it differs from siblings. 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%, so the baseline is 3. The description adds meaningful semantic value by explicitly marking state as required (the schema has no required array), specifying '2-letter US code', and giving an inline call example. This is useful beyond the property description's examples.

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 starts with a precise trigger ('Use when a user asks "what tax breaks does <state> give data centers?"') and clearly identifies the resource: data-center tax-incentive packages by US state. It further cements differentiation by explicitly stating this covers only the TAX factor for one US state, distinguishing it from analyze_site and 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?

Provides an explicit when-to-use condition, a worked example ('get_tax_incentives state=VA'), and explicit do-not-use cases with named alternatives ('analyze_site' for multi-factor reads, 'rank_markets' for cost ranking). An agent can route correctly with no inference required.

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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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