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Search investors

search_investors
Read-only

Find investors that match a startup's profile. Filter by sector_focus (e.g. 'Artificial Intelligence' for AI investors), stage_focus (Seed / Series A / etc.), geo_focus, cheque_min / cheque_max (matches investors whose cheque-size window overlaps the founder's raise), active_since (investors whose latest investment is on or after this date, to surface who has deployed capital recently), min_recent_rounds_90d (activity threshold), and actively_investing. Sort whitelist: total_score, last_investment_date, recent_rounds_90d, recent_lead_rounds_90d, total_funds_raised, min_cheque_size, max_cheque_size, last_mentioned_at, created_at. For example sort='last_investment_date.desc' surfaces the most recently active funds first. Page with offset. Needs a free StartupHub.ai account.

Input Schema

NameRequiredDescriptionDefault
qNoMatches name or description.
sortNoSort order: '<column>.<asc|desc>' from the whitelist above. Default total_score.desc. An unknown column falls back to the default.
typeNoExact, case-sensitive match on the stored investor type, for example VC, Angel, Accelerator, Corporate VC, Family Office, PE.
limitNoMax 100.
offsetNoSkip this many results, for paging.
countryNoInvestor's HQ country, exact match.
geo_focusNoGeographic region the investor targets (e.g. "US", "Europe", "Israel"). Comma-separated values must all be present.
cheque_maxNoFounder's maximum target raise: matches investors whose min_cheque_size is at most this amount
cheque_minNoFounder's minimum target raise: matches investors whose max_cheque_size is at least this amount
stage_focusNoFunding stage (e.g. 'Seed', 'Series A'). Comma-separated values must all be present.
active_sinceNoYYYY-MM-DD. Returns investors whose latest investment is on or after this date.
sector_focusNoSector the investor focuses on (e.g. 'Artificial Intelligence', 'Biotech', 'Fintech'). Comma-separated values must all be present.
actively_investingNoOnly true filters; false applies no filter.
min_recent_rounds_90dNoMinimum number of rounds in the last 90 days. Use 1+ to drop dormant funds.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed10 schema fields changed
    • addedInput schema / properties / actively_investing / description
      Added value: +"Only true filters; false applies no filter."
    • changedInput schema / properties / country / description
      Previous value: -"Investor's HQ country"New value: +"Investor's HQ country, exact match."
    • changedInput schema / properties / geo_focus / description
      Previous value: -"One geographic region the investor targets (e.g. \"US\", \"Europe\", \"Israel\")"New value: +"Geographic region the investor targets (e.g. \"US\", \"Europe\", \"Israel\"). Comma-separated values must all be present."
    • addedInput schema / properties / limit / description
      Added value: +"Max 100."
    • addedInput schema / properties / offset
      Added value: +{
+  "default": 0,
+  "description": "Skip this many results, for paging.",
+  "type": "number"
+}
    • addedInput schema / properties / q / description
      Added value: +"Matches name or description."
    • changedInput schema / properties / sector_focus / description
      Previous value: -"One sector the investor focuses on (e.g. 'Artificial Intelligence', 'Biotech', 'Fintech')"New value: +"Sector the investor focuses on (e.g. 'Artificial Intelligence', 'Biotech', 'Fintech'). Comma-separated values must all be present."
    • changedInput schema / properties / sort / description
      Previous value: -"Sort order: '<column>.<asc|desc>'. Default total_score.desc."New value: +"Sort order: '<column>.<asc|desc>' from the whitelist above. Default total_score.desc. An unknown column falls back to the default."
    • changedInput schema / properties / stage_focus / description
      Previous value: -"One funding stage (e.g. 'Seed', 'Series A', 'Series B')"New value: +"Funding stage (e.g. 'Seed', 'Series A'). Comma-separated values must all be present."
    • changedInput schema / properties / type / description
      Previous value: -"investor_type, e.g. \"Venture Capital\", \"Angel\", \"Accelerator\", \"Family Office\", \"Corporate VC\""New value: +"Exact, case-sensitive match on the stored investor type, for example VC, Angel, Accelerator, Corporate VC, Family Office, PE."
  2. Added

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint=true, destructiveHint=false, openWorldHint=false). The description adds genuine non-schema context: the auth requirement and behaviors like actively_investing=false applying no filter and min_recent_rounds_90d='Use 1+ to drop dormant funds'. It omits rate limits and the shape of returned records, so not a 5.

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?

A single dense paragraph, but front-loaded with the purpose before enumerating filters, sort whitelist, and paging. Every clause carries filter semantics; it is tight for a 14-parameter tool, though the sort whitelist list makes it heavy mid-paragraph.

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?

With 14 parameters and no output schema, the description covers all filters, their semantics, sort options, paging, and auth. It does not describe what an investor result contains, which is the only notable gap given the absent output schema.

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, but the description adds meaning beyond the schema: cheque_min/cheque_max are framed as a founder's target raise matched against overlapping cheque-size windows, active_since is justified as surfacing recently deployed capital, and sort is illustrated with a concrete example. This is real added value over the field docs.

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 a specific verb and resource ('Find investors that match a startup's profile') and immediately scopes it as a filter-driven search, which distinguishes it from sibling lookups like get_investor_by_domain, get_investor_by_social, and search_people. An agent can tell what it returns without opening the schema.

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 clear context for use (matching investors to a startup's raise profile) and states the prerequisite 'Needs a free StartupHub.ai account'. It does not name an explicit alternative such as get_investor_by_domain or find_matches, so it stops short of a full when/when-not treatment.

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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