Scheduled stock quotes, earnings and market news from Financial Modeling Prep

Fetch market data from Financial Modeling Prep (FMP) on a schedule and send it on: a pre-market quote board to Discord, yesterday's earnings beats and misses to Slack, or headlines for your watchlist by email. Three request templates cover quotes, the earnings calendar and stock news. For anything else FMP has (financial statements, analyst ratings, insider trades, SEC filings, economic data), give an AI step FMP's MCP server and let the model look it up.

#Example: yesterday's earnings, summarized for Discord

The earnings calendar step asks for the run day and the day before. Claude reads the list and writes the post, and the Discord step sends the whole reply with {{ $ }}.

{
  "name": "Earnings recap",
  "cron": { "expression": "30 8 * * 1-5", "time_zone": "America/New_York" },
  "nodes": [
    { "id": "cal", "request_template": { "template_id": "<id of fmp: Earnings calendar>", "credential_id": "YOUR_FMP_CREDENTIAL_ID", "values": { "days_back": "1", "days_ahead": "0" } } },
    { "id": "sum", "ai_generate": {
        "provider": "anthropic", "model": "claude-opus-5-5", "credential_id": "YOUR_ANTHROPIC_KEY_ID", "effort": "low",
        "system": "You write a pre-market earnings recap for traders. Format it as Discord markdown: **bold** tickers, - for lists. No tables.",
        "prompt": "These companies reported in the last day. Lead with the biggest EPS surprises either way, then list the rest in one line each. Skip rows where epsActual is null. {{ slice(sort($, \"revenueActual\", \"desc\"), 0, 40) }}",
        "text": { "max_chars": 2000 } } },
    { "id": "post", "request_template": { "template_id": "<id of discord: Send message>", "values": { "webhook_url": "https://discord.com/api/webhooks/123456789012345678/abcDEF_ghi-JKL", "content": "{{ $ }}" } } }
  ]
}

#Example: a quote board without AI

"Batch quote" returns a list, so a transform can lay it out as a table for Slack or Discord.

{
  "name": "Watchlist at the open",
  "cron": { "expression": "35 9 * * 1-5", "time_zone": "America/New_York" },
  "nodes": [
    { "id": "q", "request_template": { "template_id": "<id of fmp: Batch quote>", "credential_id": "YOUR_FMP_CREDENTIAL_ID", "values": { "symbols": "AAPL,MSFT,NVDA,^GSPC" } } },
    { "id": "t", "transform": { "format": "TRANSFORM_FORMAT_MARKDOWN_TABLE", "template": "{ \"{{#each $}}\": { \"Symbol\": \"{{ $.symbol }}\", \"Price\": \"{{ $.price }}\", \"Change %\": \"{{ $.changePercentage }}\" } }" } },
    { "id": "post", "request_template": { "template_id": "<id of slack: Send message>", "values": { "webhook_url": "https://hooks.slack.com/services/T000/B000/XXXX", "text": "{{ $ }}" } } }
  ]
}

Several symbols use FMP's batch quote, which needs a paid FMP plan. One symbol works on every plan.

#Example: an AI analyst with FMP's MCP tools

mcp_servers gives the model the tools of FMP's MCP server. Each run lists them and offers them as fmp_<tool>, such as fmp_quote, fmp_statements and fmp_news. Each tool covers a group of FMP endpoints, and the model picks one with the tool's endpoint argument. Name the tools the prompt needs in tools: each tool's description is sent to the model on every turn, so offering all 28 costs more and slows the reply.

{ "id": "brief", "ai_generate": {
    "provider": "anthropic", "model": "claude-opus-5-5", "credential_id": "YOUR_ANTHROPIC_KEY_ID", "effort": "low",
    "prompt": "Write a three-line brief on NVDA for a long-term holder: today's price move, the latest quarter against estimates, and the one headline that matters.",
    "text": { "max_chars": 2000 },
    "mcp_servers": [{
      "name": "fmp", "url": "https://financialmodelingprep.com/mcp", "credential_id": "YOUR_FMP_CREDENTIAL_ID",
      "tools": ["quote", "statements", "news", "analyst"]
    }] } }

In the job editor, add the step from Claude, OpenAI or Grok, then Financial Modeling Prep MCP under Tools. Choose the key, load the tool list, and tick the tools you want.

#Set up

1. Copy your API key from your FMP dashboard.
2. Save it as a credential. In the app, choose Financial Modeling Prep. Through the API, it's an api_key_param with param apikey and location query. It's encrypted at rest and never shown again.
3. Add an FMP step, or an AI step with the FMP MCP server, and use the credential for both.

Dates in the earnings calendar are the run's day in UTC. A job at 08:30 New York time asks for that same day.

#Stock quote: fmp_quote

Latest price, change and volume for a symbol. Sends GET https://financialmodelingprep.com/stable/quote. Output for the next step: the response body. A api_key_param or api_key_header credential, as credential_id.

Add it in the job editor with Use template on a request step. Over the API, find its id with GET /request-templates?partner=fmp&action=Stock+quote and send { "request_template": { "template_id": "<id>", "values": { … } } }; the server copies the template into the step.

#Batch quote: fmp_batch_quote

Latest price, change and volume for several symbols. Needs a paid FMP plan. Sends GET https://financialmodelingprep.com/stable/batch-quote. Output for the next step: the response body. A api_key_param or api_key_header credential, as credential_id.

Add it in the job editor with Use template on a request step. Over the API, find its id with GET /request-templates?partner=fmp&action=Batch+quote and send { "request_template": { "template_id": "<id>", "values": { … } } }; the server copies the template into the step.

#Earnings calendar: fmp_earnings_calendar

Reported and upcoming earnings, with EPS and revenue against estimates. Sends GET https://financialmodelingprep.com/stable/earnings-calendar. Output for the next step: the response body. A api_key_param or api_key_header credential, as credential_id.

Add it in the job editor with Use template on a request step. Over the API, find its id with GET /request-templates?partner=fmp&action=Earnings+calendar and send { "request_template": { "template_id": "<id>", "values": { … } } }; the server copies the template into the step.

#Latest stock news: fmp_latest_stock_news

Recent headlines across the whole market. Sends GET https://financialmodelingprep.com/stable/news/stock-latest. Output for the next step: the response body. A api_key_param or api_key_header credential, as credential_id.

Add it in the job editor with Use template on a request step. Over the API, find its id with GET /request-templates?partner=fmp&action=Latest+stock+news and send { "request_template": { "template_id": "<id>", "values": { … } } }; the server copies the template into the step.

#Stock news: fmp_stock_news

Recent headlines for chosen symbols. Sends GET https://financialmodelingprep.com/stable/news/stock. Output for the next step: the response body. A api_key_param or api_key_header credential, as credential_id.

Add it in the job editor with Use template on a request step. Over the API, find its id with GET /request-templates?partner=fmp&action=Stock+news and send { "request_template": { "template_id": "<id>", "values": { … } } }; the server copies the template into the step.