Source-cited research for your quant agent.

Add dollar-funding benchmarks, covered-bank diagnostics and market-liquidity observations to an agent's research step. Get compact tables, original source dates and explicit coverage gaps from one interface.

Get a first result

No data API key or model account is needed for this request.

curl --fail 'https://api.seiche.info/openbb/api/v1/agent-review?limit=3'

For MCP, connect https://api.seiche.info/openbb/mcp. Discover datasets, then call financial_evidence_agent_query or financial_evidence_review. Open REST documentation.

Use your existing framework

python3 -m pip install 'financial-evidence @ git+https://github.com/beepboop2025/financial-evidence-skills.git@agent-v1.0.0' langchain-core

from financial_evidence.agents import EvidenceAgentClient, framework_tools

with EvidenceAgentClient() as evidence:
    tools = framework_tools('langchain', evidence)
    print(tools[0].invoke({}))  # Offline catalog.
    # Attach tools to your researcher model and its execution node.

Native adapters support LangChain/LangGraph, CrewAI, OpenAI Agents and Pydantic AI. Plain typed Python functions work with custom researchers and schedulers. Install your chosen SDK alongside the package; your model provider has its own requirements.

Repeat checks without repeating every row

Save the response's revision and pass it as previous_revision on the same query. Identical published evidence omits duplicate rows while returning source metadata. Partial and failed retrievals always return diagnostics. Unchanged does not mean fresh. Check source dates, availability, rights and limitations on every run.

Connect an institutional research pipeline

Workflow	Useful input	Evidence boundary
TradingAgents, FinRobot, custom research agents	Funding, covered-bank and liquidity research tools	Complement existing price and fundamentals providers
Qlib, FinRL, LEAN, NautilusTrader, vectorbt	Cited captures for exploratory feature research	Validate knowledge time and vintages before backtesting
GS Quant, ArcticDB, OpenBB	Dated research tables and receipts	Integration recipes do not imply institutional adoption

Export a table with the capture example. It preserves rows and a SHA-256 receipt in a new directory. History filters select currently published observations; they do not establish what was knowable in the past.

Know the coverage

Each value retains its original date, unit, source URL, source path and content hash. Withheld or unavailable values remain missing. Bank diagnostics are research measures; market percentiles are not executable quotes. These tools supply evidence for human-reviewed research and have no trade-execution authority.

Read framework setup and quant pipeline recipes · Repository integration map · Registration demo