Financialdatapi Quantora API
53
AI ReadinessFoundational (C)53/100
Official vendor OpenAPI document · agent-readyData EnrichmentCompany DataapiKey, bearer91 EndpointsREST
For Agents
Look up company financials, SEC filings, insider trades, institutional ownership, and economic indicators, screen companies by fundamentals, and trace each figure to its source in Quantora. Authenticates with an API key in the x-api-key header or a bearer token.
Use for: Get the latest income statement and balance sheet for a public company, Find all insider trades reported for a given ticker this quarter, Screen companies trading below a price-to-earnings ratio in the technology sector, Retrieve the GDP growth indicator series for a country
Not supported: Does not execute trades, stream real-time quotes, or manage brokerage accounts. Use for retrieving company fundamentals, filings, and economic data only.
The Quantora API retrieves company fundamentals, SEC filings, insider trades, institutional ownership, and macro-economic indicators from a single financial-data backbone, so an application can pull research-grade data without stitching together separate providers. You look up an entity, company, instrument, or indicator by id or alias, read its observations and derived series, and screen companies by fundamentals or entities by macro values. A plain-language question endpoint and country briefs let an agent ask for a figure directly, while provenance and source-health endpoints trace every number back to where it came from.
Install Jentic One Beta
Connect the Quantora API to your agent
Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Quantora API, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.
Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.
1
Step 1: Jentic One Host machine
# On the machine that will host your Jentic One instance:
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Ffinancialdatapi.com%2Ffinancialdatapi" | sh2
Step 2: Agent machine
# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Ffinancialdatapi.com%2Ffinancialdatapi" | sh
jentic register # connects your agent to your Jentic One instanceJentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.
Capabilities
What an agent can do with Quantora API.
Retrieve a company's financial statements, earnings actuals, and SEC filings by id or ticker lookup
Read insider trades, institutional ownership, and beneficial-ownership events for a company
Screen companies by fundamentals, ratios, sector, and industry with the equity screener
Pull economic indicator series and country macro observations by indicator id or slug
Ask a plain-language data question and get a figure back without choosing an endpoint first
Trace any observation to its source and provider through the provenance endpoint
Use Cases
Patterns agents use Quantora API for, with concrete tasks.
★ Agent-Driven Financial Research
An AI agent connected through Jentic answers a research question by resolving the company, reading its financial statements and recent filings, and returning the figures with a provenance link, so a human never has to open a terminal or stitch provider APIs together. Because Quantora returns both raw and derived observations, the agent can report a reported number and a computed ratio in the same turn.
Resolve this ticker to a company, return its most recent revenue and net income, and include a provenance link for each figure
Equity Screening Pipeline
A screening workflow filters the company universe by fundamentals, valuation ratios, sector, and industry, then reads each match's financials to rank candidates, so an analyst gets a shortlist without manual spreadsheet work. The equity screener and its filter-field endpoint let the workflow discover which criteria are available before building the query.
Screen companies in the healthcare sector with positive earnings and return the ten with the lowest price-to-earnings ratio
Macro and Economic Monitoring
A monitoring job reads indicator series and country macro observations, watches the economic calendar for upcoming releases, and surfaces changed observations so a dashboard stays current without polling every source. Quantora's canonical and derived indicators give the job a stable identifier to track an indicator across revisions.
Retrieve the latest unemployment-rate observations for a country and list the economic calendar events due in the next seven days
Key Endpoints
91 endpoints — the quantora api retrieves company fundamentals, sec filings, insider trades, institutional ownership, and macro-economic indicators from a single financial-data backbone, so an application can pull research-grade data without stitching together separate providers.
METHOD
PATH
DESCRIPTION
GET
/companies/{idOrLookup}/financials
Get company financial statements
GET
/companies/{idOrLookup}/filings
List company SEC filings
GET
/companies/{idOrLookup}/insider-trades
Get company insider trades
GET
/equity-screener
Screen companies by fundamentals, ratios, sector, and industry
POST
/ask
Ask a plain-language data question
GET
/indicators/{indicatorId}/observations
List indicator observations
GET
/economic-calendar
List economic calendar events
GET
/companies/{idOrLookup}/financials
Get company financial statements
GET
/companies/{idOrLookup}/filings
List company SEC filings
GET
/companies/{idOrLookup}/insider-trades
Get company insider trades
GET
/equity-screener
Screen companies by fundamentals, ratios, sector, and industry
POST
/ask
Ask a plain-language data question
GET
/indicators/{indicatorId}/observations
List indicator observations
GET
/economic-calendar
List economic calendar events
Jentic AI Readiness Score
This API is usable in Jentic One now. Its AI-readiness score against Jentic's framework shows where it stands today and where improvements would make it even easier for agents to use.
Q
Quantora API
- Foundational (C)53/100
57
Foundational Compliance62
Developer Experience & Jentic Compatibility45
AI-Readiness & Agent Experience87
Agent Usability55
Security31
AI DiscoverabilityPowered by JenticScoring Framework 1.0.0 | Scoring Engine 0.4.2
Show dimension breakdown
57
Foundational Compliance
Base layer of spec validity and structural soundness.
Grade: C+Signals: 4
68%
Lint Results
Aggregated quality score from linter diagnostics, weighted by severity.
100%
Resolution Completeness
Percentage of `$ref` references that resolve successfully.
0%
Specification Validity
Checks whether the API description parses successfully and conforms to its declared specification (e.g., OpenAPI).
60%
Structural Integrity
Structural correctness score based on schema issues using logarithmic dampening.
62
Developer Experience & Jentic Compatibility
Clarity, completeness, and ingestion readiness for developers and tooling.
Grade: B-Signals: 4
0%
Example Density
How richly the API is illustrated with examples.
100%
Example Validity
Percentage of examples that conform to their schemas.
49%
Response Coverage
Percentage of operations with complete response definitions (success, client error, server error).
100%
Tooling Readiness
Health of API ingestion, bundling, and resolution within Jentic pipelines.
45
AI-Readiness & Agent Experience
Semantic breadth, depth, and agent comprehension for AI systems.
Grade: DSignals: 4
29%
Description Coverage
Coverage of descriptions across API elements.
0%
Error Standardization
Coverage of RFC 9457 Problem Details for error responses.
100%
OperationId Quality
Coverage, uniqueness, and casing consistency of operationIds for AI inference.
50%
Summary Coverage
Coverage of summaries across operations/tags/info.
87
Agent Usability
Functional utility, complexity comfort, and AI orchestration readiness.
Grade: ASignals: 1
87%
Complexity Comfort
Agent comfort level based on API operational and structural complexity.
55
Security
Trust, risk posture, and security compliance.
Grade: CSignals: 1
55%
Authentication Strength
Average quality of security schemes based on authentication method strength (weakest link for OAuth2).
31
AI Discoverability
Findability, semantic richness, and reasoning readiness.
Grade: FSignals: 1
31%
Descriptive Richness
Clarity and depth of descriptions across API elements.
Score it yourself
Every API in the directory is allowlisted, so you can re-score it with no key required.
npx @jentic/api-scorecard-cli score <openapi-url>Why Jentic?
What agents get from Jentic-routed access to this vendor.
Setup
Wiring the Quantora API by hand means handling its x-api-key or bearer auth, learning which id-or-slug lookups each resource accepts, and paging long observation series yourself. Through Jentic you install once, import Quantora from the API Directory, store the key once, and your agent calls it.
Permission scoping
Quantora is a read-only data API, so you choose which read operations your agent may call: you can allow company and indicator lookups while leaving operational and admin endpoints out. Rules bound which operations run, so the agent reads data and cannot reach anything you did not grant.
Credential isolation
Your Quantora key is stored once, encrypted, by your own Jentic One instance and injected at execution time. It never enters the agent's prompt, logs, or context.
Intent-based discovery
Agents search Jentic by intent such as 'get company financials' or 'screen companies by fundamentals', and Jentic returns the matching Quantora operation with its input schema so the agent calls the right endpoint without browsing the reference docs.
Related APIs
Alternatives and complements available in the Jentic catalogue.
FAQs
Specific to using Quantora API through Jentic.
Is there a Quantora MCP server?
You don't need an MCP server to give your agent the Quantora API. Jentic connects it directly from the API Directory: import it, store your key once, and your agent can look up company financials, screen equities, and read economic indicators straight away, with no extra server to run and no tool definitions sitting in the agent's context.
Can I limit what my agent is allowed to do with the Quantora API?
Yes. Quantora is a read API, so you can write a rule that allows only the lookups the agent needs, such as reading company financials and economic indicators, and leaves screening or operational endpoints out. Every call the agent makes is logged, so you can see exactly which figures it pulled.
What authentication does the Quantora API use?
The Quantora API authenticates with an API key sent in the x-api-key header, or a bearer token, per its OpenAPI spec. A few operational endpoints such as the health and readiness checks need no credential. Through Jentic the key is stored encrypted by your own instance and added at call time, so it never appears in the agent's prompt or logs.
Can I screen companies by fundamentals with the Quantora API?
Yes. The equity screener filters companies by fundamentals, ratios, sector, and industry, and a companion filter-fields endpoint lists which criteria you can query. An agent can discover the available filters, build a screen, and then read each match's financial statements to rank the results.
What are the rate limits for the Quantora API?
The OpenAPI spec does not state request rate limits for the Quantora API, though it exposes a rate-limit policy endpoint you can read at runtime. For current published limits and fair-use guidance, check the provider documentation at https://api.financialdatapi.com.
How do I pull a company's financials through Jentic?
Import the Quantora API from the Jentic API Directory, then have your agent issue a request such as 'get the latest income statement for this company'. Jentic matches the intent to the company-financials operation and returns its input schema so the agent builds the correct request, with your stored key injected at call time. To run it on your own infrastructure, install Jentic One from its GitHub repo.
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