Financial data API comparison

The financial-data API built for AI agents

Arkolith vs Financial Datasets, Financial Modeling Prep, and Octagon. An honest read on which tool fits which job, so your agent points at the right ground truth.

The one-paragraph verdict

Financial Datasets, FMP, and Octagon are broad. They cover prices, fundamentals, crypto, and, in Octagon's case, an AI research layer over private and public markets. If your agent needs wide market coverage, they are strong choices. Arkolith is deliberately the other shape: deep on the SEC ownership cluster (13F holdings, Form 4 insiders, and Congressional trades), with per-datapoint provenance, a point-in-time archive, resolved amendment chains, and a cross-source confluence signal you can call as one tool. It is MCP-native and first-party, and it never runs inference, so every call is a fast, sourced lookup your own agent reasons over.

Choose by the job

JobBest fitWhy
AI agent needs a sourced answer about ownershipArkolithMCP plus REST, filing provenance, resolved entities, and public pages for human verification.
One vendor for prices, fundamentals, crypto, and broad market dataFinancial Datasets or FMPThey are broader feeds. Arkolith is intentionally deep on EDGAR ownership and insiders.
AI research answer with generated narrativeOctagon or a research agentArkolith returns sourced data rows and does not run inference inside the data bill.
Raw legal source reviewSEC EDGAR directUse the primary filing document when the task is legal review or complete document inspection.

Drill into the data family

Use these narrower comparisons when the question is not broad financial data, but a specific SEC-derived dataset and how an agent should cite it.

Side by side

Compiled from public documentation, July 2026. Products change, so verify current specifics with each vendor.

CapabilityArkolithFinancial DatasetsFMPOctagon
First-party MCP server
YesNative, metered per call
YesOfficial MCP
PartialCommunity wrappers
YesOfficial MCP
Per-datapoint provenance (field to source + timestamp)
YesEvery field traced
PartialFiling / source level
PartialSource links
PartialSource-backed answers
Point-in-time / as-of (as-known-on)
YesBitemporal archive
PartialReport-period filters
PartialFiling dates
NoResearch answers
Amendment / supersession resolved
Yes13F & Form 4 chains
NoLatest filing
NoLatest filing
NoNot documented
Cross-source confluence signal (13F x insider x Congress)
YesShipped as a tool
NoRaw feeds only
NoRaw feeds only
PartialVia research agent
Congress / STOCK Act trades
YesFree tool (compliance-gated)
NoNot documented
YesSenate + House
NoNot documented
Runs its own inference (you pay token cost)
NoPure data lookup
NoData API
NoData API
YesAI research credits
Broad market data (prices, crypto, fundamentals, private / VC)
NoDeep on ownership, not broad
YesBroad coverage
YesBroad coverage
YesBroad + research
Pricing model
PartialPrepaid credits, $5 min
Partial$200 / $2,000 + PAYG
PartialTiered API plans
PartialResearch credits

Choose Arkolith when

  • Your agent needs to cite a number, not guess it (per-datapoint provenance)
  • You reason over ownership: who is buying, before consensus (13F, Form 4, Congress)
  • You need point-in-time truth, not just the latest snapshot
  • You want a confluence signal across sources as one call
  • You do not want to pay a model token cost inside your data bill

Choose a broad provider when

  • You mainly need real-time prices, quotes, or crypto
  • You need broad fundamentals and analyst estimates across thousands of tickers
  • You want private-company, funding, or VC coverage (Octagon)
  • You want an AI research layer that returns synthesized answers (Octagon)
  • One broad feed is simpler than composing best-of-breed sources

Why the ownership cluster is different

Provenance

Every field is traced to its source filing and timestamp, so an agent can cite it and a human can verify it.

Point-in-time

Query a book as it was known on a past date. Backtests and audits stop leaking future information.

Amendments resolved

A restated 13F or corrected Form 4 supersedes the original, so positions are not double-counted.

Confluence signal

Crowding across 13F, insider, and Congressional activity, composed into one tool call.

One key, one call

Connect the MCP server to your agent, or hit REST directly. Same data, same provenance, metered by prepaid credits.

# REST: latest resolved 13F holdings for a filer, with provenance
curl -H "Authorization: Bearer $ARKOLITH_KEY" \
  "https://arkolith.com/api/v1/funds/1067983/holdings"

# MCP: connect once, then your agent calls tools like
#   fund.holdings, insider.recent, signal.confluence, provenance.get
#   https://arkolith.com/api/mcp

Frequently asked questions

Which financial data API is best for AI agents?

It depends on what the agent needs. For broad market data (prices, fundamentals, crypto, private companies) Financial Datasets, FMP, and Octagon cover more surface. For deep, verifiable SEC ownership data (13F holdings, Form 4 insiders, Congressional trades) with per-datapoint provenance, point-in-time access, and cross-source signals, Arkolith is purpose-built. Many teams use a broad API for prices and Arkolith for ownership and signals.

What makes Arkolith different from Financial Datasets or FMP?

Three things. Every datapoint carries provenance to its source filing and timestamp, so an agent can cite it and a human can verify it. The archive is point-in-time, so you can ask what a book looked like as it was known on a past date, not just today. And amendment chains are resolved, so a restated 13F or a corrected Form 4 supersedes the original instead of double-counting. Arkolith also ships a confluence signal that crowds 13F, insider, and Congressional activity into one tool.

Does Arkolith run inference like Octagon?

No. Octagon is a research-answer layer that runs its own AI agents and bills research credits. Arkolith never runs inference. Your agent (Claude, Codex, or another) calls Arkolith as a tool and does its own reasoning, so you never pay a model token cost inside our pricing and every call is a fast, sourced data lookup.

Is Arkolith MCP-native?

Yes. Arkolith exposes a first-party MCP server and a REST API over the same data, with per-key auth and metered credits. Connect it to Claude Code or any MCP client, or call REST directly. Financial Datasets and Octagon also ship official MCP servers; FMP is reachable through community MCP wrappers.

When should I NOT use Arkolith?

If your agent mainly needs real-time prices, crypto, broad fundamentals, or private-company and VC data, a broad provider like Financial Datasets, FMP, or Octagon fits better. Arkolith is deliberately deep rather than broad: the EDGAR ownership cluster (13F, Form 4, Congress) with the cross-source join as the moat.

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