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// // autogen integration

Market data tools for
AutoGen agents.

TickerDB exposes pre-computed financial data as MCP tools. AutoGen's MCP support lets your agents call market data tools directly — trend analysis, valuation checks, ticker event history, and more.

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// setup

Connect in a few lines.

AutoGen supports MCP tool servers over streamable HTTP. Point it at TickerDB's remote MCP server, and your agents get access to all available market data tools.

python 
# Connect AutoGen to TickerDB's MCP server
from autogen_ext.tools.mcp import StreamableHttpServerParams, mcp_server_tools

server_params = StreamableHttpServerParams(
    url="https://mcp.tickerdb.com/mcp",
    headers={"Authorization": "Bearer tdb_your_api_key"},
)

tools = await mcp_server_tools(server_params)

# Every tool is now available to your agents
// agent workflow

Multi-agent market analysis.

AutoGen's multi-agent conversations get richer with real market data. Give your agents TickerDB tools and they can pull summaries, use summary event mode for historical context, and monitor watchlists — passing context between agents automatically.

python 
# Give an AutoGen agent market data tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.tools.mcp import StreamableHttpServerParams, mcp_server_tools

server_params = StreamableHttpServerParams(
    url="https://mcp.tickerdb.com/mcp",
    headers={"Authorization": "Bearer tdb_your_api_key"},
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="market_analyst",
    model_client=model_client,
    tools=tools,
)

result = await agent.run(
    task="Get a summary of AAPL and check its historical oversold events"
)
// state changes

Track state changes effortlessly.

Most market data APIs return point-in-time snapshots. TickerDB tracks state transitions — your agent sees what changed, not just what is.

python 
# Ask the agent to check for state changes
result = await agent.run(
    task="Check my watchlist for state changes and summarize what moved"
)
json 
{
  "timeframe": "daily",
  "run_date": "2026-03-28",
  "changes": {
    "AAPL": [
      {
        "field": "rsi_zone",
        "from": "neutral",
        "to": "oversold"
      },
      {
        "field": "trend_direction",
        "from": "uptrend",
        "to": "downtrend"
      }
    ]
  },
  "ticker_context": {
    "AAPL": {
      "last_changed_date": "2026-03-28"
    }
  },
  "tickers_checked": 2,
  "tickers_changed": 1
}
// what your agent sees

What your agent sees.

Every tool returns categorical facts — not raw OHLCV data. Your agent can branch on "oversold" without needing to know what RSI > 70 means.

json 
{
  "ticker": "NVDA",
  "data_status": "eod",
  "as_of_date": "2026-04-11",
  "trend": {
    "direction": "strong_uptrend",
    "ma_alignment": "aligned_bullish"
  },
  "momentum": {
    "rsi_zone": "overbought",
    "macd_state": "expanding_positive",
    "direction": "accelerating"
  },
  "volatility": {
    "regime": "normal",
    "regime_trend": "stable"
  },
  "fundamentals": {
    "valuation_zone": "fair_value",
    "pe_vs_historical_zone": "premium",
    "last_earnings_surprise": "beat"
  }
}
// available tools

What your agent can call.

Every tool returns pre-computed market-state data: categorical facts plus supporting metadata your agent can reason about immediately.

get_summary

Full market-state snapshot for a single asset: trend, momentum, volatility, volume, extremes, fundamentals, and support/resistance.

get_search

Multi-field filtering across all assets. Build complex queries with arbitrary filter combinations.

get_schema

All queryable fields with types, values, and descriptions. Always free.

get_watchlist

Latest EOD summary data for all tickers in your saved watchlist.

get_watchlist_changes

Field-level diffs for your watchlist since the last pipeline run.

create_webhook

Register a webhook URL for watchlist change notifications.

list_webhooks

List your registered webhook URLs.

delete_webhook

Remove a registered webhook.

full tool reference
// why tickerdb + autogen

Built for how agents actually work.

Categorical, not numerical

TickerDB returns "rsi_zone": "oversold" instead of raw RSI values. Your AutoGen agents reason on categories they already understand — no prompt engineering required.

Pre-computed

Our data is computed once daily after market close and cached. Your agents get instant responses with zero request-time computation.

Tiny context footprint

A TickerDB response uses a fraction of the tokens you'd need to pass raw OHLCV data. More room for reasoning, less spent on input.

Start building.

Try for free. No credit card required.

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