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Finterm.ai
FreemiumSelf-Hosted
Trading agents built on raw API calls drown in noise — syndicated reprints, AI-generated summaries, and duplicate earnings releases that eat context and skew signals before a single decision gets made. Finterm is the CLI data layer built to strip that noise before it reaches your agent.
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Summary
Finterm installs as a global npm package and exposes financial data through structured CLI commands that any agent running a shell can call. One command returns a full ticker snapshot — earnings actuals, ratios, options sentiment, short pressure, technicals — without stitching five APIs together. The SEC filing diff tool compares quarters section by section and returns changed language, not full documents, so the agent sees only what moved. The deep research bundle crawls 600–800 sources per ticker and drops the ~30–40% that is noise before output reaches the agent. There is no API surface — if your agent cannot run a CLI, you cannot use Finterm.
Bottom line: Finterm earns its place in a Claude Code or ChatGPT-backed trading agent where the bottleneck is structured, deduplicated financial input — but if your infrastructure cannot invoke a shell command or you need a REST endpoint, you are looking at the wrong tool.
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Pros
- Single-call ticker bundles that return earnings, ratios, options sentiment, short pressure, and technicals together — so the agent does not need to stitch five separate data sources and the context stays clean.
- SEC filing diffs that surface only changed language between two quarters, which means the agent reads the delta rather than ingesting two full documents to find it.
- Source deduplication and quality labeling on the deep research bundle, so AI-generated summaries and syndicated reprints are dropped before output reaches the agent's context window — a failure mode that silently corrupts analysis when left unaddressed.
- Structured YAML and JSON output natively, so the agent receives data it can act on without a parsing step.
- CLI delivery works with any agent that can invoke a shell command, which means integration with Claude Code or ChatGPT tool use does not require a custom SDK.
Cons
- No API surface exists. Any agent architecture built around HTTP requests — LangChain tool definitions, n8n HTTP nodes, or standard REST integrations — cannot use Finterm without a shell invocation layer in between. Teams with API-first stacks build a wrapper or switch to a data provider that exposes endpoints.
- Deep research bundles are thorough by design, crawling hundreds of links per run. That is the right tradeoff for a weekly research pass, but it is the wrong tradeoff for a latency-sensitive agent that needs to react to an intraday event inside seconds. Teams needing sub-second data access use a streaming market data API alongside or instead of Finterm.
- Support runs through a Discord community with no indication of SLA-backed channels. A production trading agent that hits an undocumented edge case at market open has no escalation path beyond the community — teams with uptime requirements evaluate this as a vendor risk before committing.
About
- Platforms
- CLI, npm
- API Available
- No
- Self-Hosted
- Yes
- Last Updated
- July 14, 2026
Best For
Who it's for
- AI trading agents needing structured financial inputs
- Agents requiring sourced and timestamped market data
- CLI-based workflows for finance data retrieval
What it does well
- Retrieving comprehensive ticker data bundles including earnings and ratios
- Comparing SEC filings section by section with diffs
- Running deep research with source deduplication and labeling
- Analyzing options sentiment and insider flows
- Scoring ticker sentiment against historical benchmarks
Integrations
Frequently Asked Questions
- Is Finterm.ai free?
- Finterm.ai offers a free option alongside paid upgrades. Check the current allowances and terms before choosing a plan.
- Can I self-host Finterm.ai?
- Yes. Finterm.ai supports self-hosting on your own infrastructure.
- What platforms does Finterm.ai support?
- Finterm.ai is available on: CLI, npm.
Trading agents that pull raw financial data run into the same wall: the context window fills with boilerplate, syndicated reprints, and stale guidance before any signal arrives. Finterm installs via npm and sits between that noise and your agent, exposing bundles and tools over CLI that return structured YAML or JSON your agent can consume in a single call. The core workflow is a command, a ticker, and a delivery mode — the tool does the fetching, filtering, deduplication, and structuring.
The differentiating feature is the source-quality pass on the deep research bundle. The vendor describes a crawl of 600–800 links per ticker followed by a deduplication and labeling step that drops AI-generated summaries, SEO spam, and syndicated reprints — the page cites roughly 30–40% of crawled links stripped as noise. What reaches the agent is labeled primary or secondary, and duplicate earnings releases across multiple sites are merged into one entry. That means the agent’s context reflects what the market actually published, not how many outlets copy-pasted the same press release.
Finterm fits CLI-based agent pipelines — Claude Code, ChatGPT with tool use, or custom agents that can invoke shell commands. The SEC filing diff tool returns only the changed language between two quarters, which is meaningfully different from passing a full 10-Q to a model and asking it to find the delta. Where Finterm breaks: there is no API, so any agent architecture that expects an HTTP endpoint is blocked at the integration step. The vendor states self-hosting is available, but the absence of an API surface is a structural constraint, not a configuration option.
Installation is a single npm command. The CLI works wherever your agent can run a shell. Delivery modes include inline results and summary JSON, giving agents a choice between immediate structured output and a file artifact. The docs describe a Discord community for support, which is the primary support channel — there is no indication of dedicated enterprise support tiers.
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