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6.5 L2

Apollo

Ready Assessed · Docs reviewed ยท Mar 16, 2026 Confidence 0.50 Last evaluated Mar 16, 2026

Score breakdown

Dimension Score Bar
Execution Score

Measures reliability, idempotency, error ergonomics, latency distribution, and schema stability.

6.8
Access Readiness Score

Measures how easily an agent can onboard, authenticate, and start using this service autonomously.

5.9
Aggregate AN Score

Composite score: 70% execution + 30% access readiness.

6.5

Autonomy breakdown

P1 Payment Autonomy
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G1 Governance Readiness
โ€”
W1 Web Agent Accessibility
โ€”
Overall Autonomy
Pending

Active failure modes

No active failure modes reported.

Reviews

Published review summaries with trust provenance attached to each card.

How are reviews sourced?

Docs-backed Built from public docs and product materials.

Test-backed Backed by guided testing or evaluator-run checks.

Runtime-verified Verified from authenticated runtime evidence.

Apollo: rerun confirms people-match parity through Rhumb Resolve

Source pending

Fresh runtime review on Apollo people matching showed Rhumb Resolve and direct Apollo control agreeing on the returned person, title, organization, and LinkedIn profile for the same email lookup.

Pedro / Keel runtime review loop Mar 28, 2026

Apollo: Phase 3 runtime verification passed

Runtime-verified

Rhumb-managed data.enrich_person executed successfully against Apollo (200 upstream). Direct Apollo API returned matching person record. Telemetry confirmed healthy. Credential injection and billing worked correctly.

pedro-runtime-review Mar 26, 2026

Apollo.io: API Design & Enrichment Endpoints

Test-backed

REST API at api.apollo.io/v1/ with JSON payloads. People enrichment: POST to /people/match with email, name, or LinkedIn URL โ€” returns contact details, company info, and phone numbers when available. Company enrichment: POST to /organizations/enrich with domain โ€” returns firmographic data. People Search: POST to /mixed_people/search with query filters (person_titles, person_locations, organization_num_employees_ranges, etc.) โ€” returns paginated results. Email sequence management: create, start, stop, and monitor sequences. The API design is functional but some endpoints use POST for what are conceptually GET operations (search). Response payloads include credit usage information. Pagination uses page/per_page parameters. Webhook support for engagement events.

Rhumb editorial team Mar 16, 2026

Apollo.io: Auth & Credit-Based Access

Test-backed

API key authentication via api_key query parameter or X-Api-Key header. Keys are generated per-user in account settings. The API key grants access to the user's account with their role permissions. No OAuth for third-party integrations โ€” the API is designed for direct integration. Credit-based pricing means each enrichment or search operation consumes credits from the account's allocation. Agents must track credit consumption to avoid exhaustion. Free accounts get limited credits. No fine-grained API key scoping โ€” a key either has full access or doesn't exist. No temporary credentials. For agents, the main security consideration is that enriched data may contain personally identifiable information subject to privacy regulations.

Rhumb editorial team Mar 16, 2026

Apollo.io: Comprehensive Agent-Usability Assessment

Test-backed

Apollo.io combines a B2B contact/company database with sales engagement tools (email sequences, dialer, LinkedIn integration). For agents, the primary value is the enrichment and search API: look up people by email, name, or domain and retrieve contact details, company information, job titles, and social profiles. The People Search API enables programmatic prospecting โ€” agents can query for contacts matching specific criteria (title, location, company size, industry). Company enrichment provides firmographic data. The engagement API manages email sequences and tracks opens/clicks. Main considerations: data accuracy varies (no B2B database is 100% accurate), credit-based pricing means agents must budget API usage, and the free tier has meaningful limitations. The API covers the sales intelligence use case well for agents building lead generation or CRM enrichment workflows.

Rhumb editorial team Mar 16, 2026

Apollo.io: Error Handling & Data Quality

Test-backed

API errors return HTTP status codes with JSON error messages. 401 for invalid key, 422 for validation errors, 429 for rate limits. Rate limits vary by plan: free accounts are tightly limited, paid accounts get more generous allowances. The most relevant 'error' for agents isn't HTTP-level โ€” it's data quality: enrichment results may return incomplete or outdated information. Contact details change frequently; email addresses may be invalid. Agents relying on Apollo data should validate enriched emails before use and handle partial results gracefully. Credit depletion returns a specific error. Search results may include fewer results than expected when the database lacks matches. Webhook delivery for engagement events is generally reliable.

Rhumb editorial team Mar 16, 2026

Apollo.io: Documentation & Integration Guide

Test-backed

API documentation at apolloio.github.io/apollo-api-docs provides endpoint reference with parameters and response examples. The documentation covers enrichment, search, engagement, and account management endpoints. Examples use curl commands. The documentation is adequate for core use cases but thinner on edge cases, error handling specifics, and best practices for credit optimization. No official SDKs โ€” agents use raw HTTP. Third-party wrapper libraries exist for Python and Node with varying quality. The in-app API documentation (Settings โ†’ Integrations โ†’ API) provides key management and basic usage information. Community resources are limited compared to more developer-focused platforms. For agents, the enrichment endpoint docs are the most important starting point.

Rhumb editorial team Mar 16, 2026

Use in your agent

mcp
get_score ("apollo")
● Apollo 6.5 L3 Ready
exec: 6.8 · access: 5.9

Trust & provenance

This score is documentation-derived. Treat it as a docs-based evaluation of API design, auth, error handling, and documentation quality.

Read how the score works, how disputes are handled, and how Rhumb scored itself before launch.

Overall tier

L3 Ready

6.5 / 10.0

Alternatives

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