AIsa Go-To-Market

Organization Search

post_apollo_mixed_companies_search

Read-onlyIdempotent

Find companies matching criteria: name, domain, headcount, industry, location, funding stage and technologies in use. Returns organizations and accounts side by side — organizations are Apollo's global database, accounts are records that already exist in this Apollo workspace — plus pagination and breadcrumbs echoing the filters that were applied. Use it to build a target list. When you already know the domain, get_apollo_organizations_enrich answers directly and costs less.

Input Schema

TableJSON Schema

Name	Required	Description
`page`	No	The page number of the Apollo data that you want to retrieve. Use this parameter in combination with the per_page parameter to make search results for navigable and improve the performance of the endpoint. Example: 4
`per_page`	No	The number of search results that should be returned for each page. Limiting the number of results per page improves the endpoint's performance. Use the page parameter to search the different pages of data. Example: 10
`revenue_range`	No
`organization_ids`	No	The Apollo IDs for the companies you want to include in your search results. Each company in the Apollo database is assigned a unique ID. To find IDs, identify the values for organization_id when you call this endpoint. Example: 5e66b6381e05b4008c8331b8
`q_organization_name`	No	Filter search results to include a specific company name. If the value you enter for this parameter does not match with a company's name, the company will not appear in search results, even if it matches other parameters. Partial matches are accepted. For example, if you filter by the value marketing, a company called NY Marketing Unlimited would still be eligible as a search result, but NY Market Analysis would not be eligible. Example: apollo or mining
`total_funding_range`	No
`organization_locations`	No	The location of the company headquarters. You can search across cities, US states, and countries. If a company has several office locations, results are still based on the headquarters location. For example, if you search chicago but a company's HQ location is in boston, any Boston-based companies will not appearch in your search results, even if they match other parameters.. To exclude companies based on location, use the organization_not_locations parameter. Examples: texas; tokyo; spain
`latest_funding_date_range`	No
`q_organization_job_titles`	No	The job titles that are listed in active job postings at the company. Examples: sales manager; research analyst
`organization_job_locations`	No	The locations of the jobs being actively recruited by the company. Examples: atlanta; japan
`organization_not_locations`	No	Exclude companies from search results based on the location of the company headquarters. You can use cities, US states, and countries as locations to exclude. This parameter is useful for ensuring you do not prospect in an undesirable territory. For example, if you use ireland as a value, no Ireland-based companies will appear in your search results. Examples: minnesota; ireland; seoul
`latest_funding_amount_range`	No
`organization_num_jobs_range`	No
`q_organization_domains_list`	No	The domain name for the person's employer. This can be the current employer or a previous employer. Do not include www., the @ symbol, or similar. This parameter accepts up to 1,000 domains in a single request. Examples: apollo.io; microsoft.com
`q_organization_keyword_tags`	No	Filter search results based on keywords associated with companies. For example, you can enter mining as a value to return only companies that have an association with the mining industry. Examples: mining; sales strategy; consulting
`organization_job_posted_at_range`	No
`organization_num_employees_ranges`	No	The number range of employees working for the company. This enables you to find companies based on headcount. You can add multiple ranges to expand your search results. Each range you add needs to be a string, with the upper and lower numbers of the range separated only by a comma. Examples: 1,10; 250,500; 10000,20000
`currently_using_any_of_technology_uids`	No	Find organizations based on the technologies they currently use. Apollo supports filtering by 1,500+ technologies. Apollo calculates technologies data from multiple sources. This data is updated regularly. Check out the full list of supported technologies by downloading this CSV file . Use underscores (_) to replace spaces and periods for the technologies listed in the CSV file. Examples: salesforce; google_analytics; wordpress_org

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedSep 15, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds genuinely useful behavioral detail: the side-by-side organizations/accounts return structure, pagination, and breadcrumbs that echo applied filters. It does not discuss rate limits or data freshness, but the annotations carry most of the safety burden.

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

Conciseness5/5

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

Three sentences deliver action, return format, and usage guidance with zero filler. The key behavior is front-loaded and the sibling routing comes last, making the description easy to scan.

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 complex 18-parameter, 0-required-field search tool, the description covers what the tool does, what it returns, how results are scoped, and when to prefer a cheaper sibling. The output schema and rich input schema cover the remaining details, so nothing an agent needs to invoke it correctly is missing.

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?

The description provides a high-level summary of filter categories ('name, domain, headcount, industry, location, funding stage and technologies'), which helps orient an agent but adds no syntax, formatting, or interaction details beyond what the input schema already documents. With 67% schema description coverage, the schema does most of the parameter-level heavy lifting, so the baseline 3 is appropriate.

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 opens with a specific verb ('Find companies matching criteria') and enumerates the filter dimensions, so an agent immediately knows what this tool does. It also clarifies the unusual 'mixed' behavior: results include both Apollo's global organizations and workspace-specific accounts, which distinguishes it from a simple company search. The explicit contrast with get_apollo_organizations_enrich further disambiguates it from a close sibling.

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?

The description states the intended use case directly: 'Use it to build a target list.' It also names the alternative and gives the exact condition for choosing it: 'When you already know the domain, get_apollo_organizations_enrich answers directly and costs less.' This is clear when-to-use and when-to-use-something-else guidance.

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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