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Glama

venturepulse

Access startup funding intelligence: search VC rounds, match with investors, score pitch decks, decode term sheets, and model cap tables. Global coverage.

Instructions

VenturePulse: Startup funding intelligence API. VC round data, investor matching, pitch deck scoring, term sheet decoding, cap table modeling, global accelerator directory, market sizing, legal formation, comparabl

Coverage: Global

Endpoints: • funding-search ($0.10): VC funding round intelligence • investor-match ($0.15): Investor matching engine • pitch-score ($0.20): Pitch deck scoring • term-sheet ($0.20): Term sheet decoder • cap-table ($0.15): Cap table dilution modeler • accelerator ($0.10): Global accelerator directory • market-size ($0.15): TAM/SAM/SOM market size analysis • legal-formation ($0.15): Startup legal formation guide • comparable ($0.10): Comparable deal benchmarks • due-diligence ($0.15): Investor due diligence prep

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langNoen | es | fr | de | ja | pt | it | nl | ko | zh | ar
focusNolegal | financial | technical | all
stageNopre-seed | seed | series-a | series-b | growth | any
termsNoPaste the full term sheet text or describe specific clauses to decode
actionYesWhich endpoint to call. Options: funding-search | investor-match | pitch-score | term-sheet | cap-table | accelerator | market-size | legal-formation | comparable | due-diligence
regionNous | eu | uk | apac | latam | mena | africa | global
sectorNofintech | saas | biotech | ai | climate | consumer | b2b | deeptech | any
countryNoUS | UK | CA | AU | SG | IE | DE | FR | IN | BR | NL | SE | IL | NZ | JP | KR
is_safeNotrue | false — whether this is a SAFE note
approachNotop-down | bottom-up | both
geographyNoglobal | us | eu | uk | apac | latam | mena | africa | specific country
raise_usdNoAmount being raised in USD — e.g. 2000000
structureNopriced | safe | note
check_sizeNoTarget check size in USD — e.g. 500000
equity_maxNoMaximum equity percentage willing to give up — e.g. 7
descriptionNoPlain English description of your startup — what it does, for whom, how it makes money
founders_pctNoCurrent founder ownership percentage — e.g. 80
pre_money_usdNoPre-money valuation in USD — e.g. 8000000
target_marketsNoWhere you plan to sell — e.g. US, EU
option_pool_pctNoCurrent option pool percentage
founder_locationsNoWhere founders are located — e.g. US, Germany (default: same as country)
existing_investors_pctNoExisting investor ownership percentage
option_pool_increase_pctNoNew option pool percentage required by investors

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

C2.8/5.0
Behavior2/5

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It mentions global coverage and per-call pricing but does not disclose data sources, expected output format, rate limits, authentication needs, or side effects. Given this is a data/API tool, users are left inferring read-only behavior and output characteristics.

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

Conciseness3/5

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

The description front-loads the core purpose but then expands into a long, bulleted list of endpoints with pricing. While structured, it is verbose and repeats some information found in the schema (e.g., endpoint names in the action enum). The length is somewhat justified by the number of endpoints, but it could be tighter with a summary paragraph.

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

Completeness2/5

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

With 23 parameters, 10 actions, no annotations, and no output schema, the description is not adequate. It lists endpoints and pricing but fails to explain how to select actions, what inputs are needed per action, what the output or response looks like, or any examples. A user would need external documentation to effectively use this tool, so completeness is low given the complexity.

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 parameters are already well-documented individually. The description adds endpoint-specific pricing and high-level purpose (e.g., 'term sheet decoder') but does not add further parameter-level semantics or examples. Baseline 3 is appropriate as the description offers marginal extra value beyond the schema.

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

Purpose4/5

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

The description clearly states this is a 'Startup funding intelligence API' and enumerates specific capabilities like VC round data, investor matching, and pitch deck scoring. It distinguishes itself from sibling tools by focusing on startup funding, though the purpose is buried under a long listing of endpoints and pricing rather than a crisp single-sentence definition.

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

Usage Guidelines2/5

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

The description lists endpoints but provides no guidance on when to use this tool versus alternatives, nor when to choose one endpoint over another. There is no mention of use cases, prerequisites, or exclusions. The enum for 'action' implies choices but the description doesn't explain the decision context.

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