Fodda Earnings Intelligence is the official remote MCP server from fodda.ai. It answers at https://mcp.fodda.ai/earnings-intelligence over streamable HTTP and asks you to sign in with your fodda.ai account before it lists its tools, so your client opens a login the first time it connects. Our probes reached it 10 of 10 times since 4 September 2026; the last check, on 17 October 2026, got the sign-in challenge, so it is up.
Cross-company earnings trends & executive divergence with citable sources.
Description as the publisher wrote it.
| Tool | What it does |
|---|---|
generate_visual | Create a presentation-ready data visualization from research findings. Available chart types: "cultural_shifts" (From→To transitions), "competitive_compass" (brands on 2 axes), "trend_constellation" (network of related trends), "implication Inputs: chart_type, data |
get_capabilities | Returns Fodda's main capabilities / features / offerings / products / services / tools and how to use them. Call this for any question about what Fodda can do or what's available. Inputs: userId |
get_company_earnings | The canonical per-ticker earnings source. Returns the full truth-layer record for covered tickers (517 consumer-sector companies) — analyst concerns, sentiment labels, strategic activity (marketing/retail/technology/sustainability), CEO int Inputs: mode, view, ticker, tickers, period, metrics |
get_earnings_divergence | Cross-company analyst-management divergence detection from the knowledge graph (legacy-thematic). Surfaces where executives are deflecting, reframing, or avoiding specific topics — the gap between what analysts press on and how management r Inputs: sector, industry, search, dateFrom, dateTo, limit |
get_earnings_intelligence | Cross-company thematic earnings intelligence from the knowledge graph and web sources. Use for multi-company comparisons ("what are hotel companies saying about labor costs?"), industry-level queries, or sector filters. For single-brand ear Inputs: ticker, brand, industry, sector, search, dateFrom |
get_evidence | Get the source articles, case studies, and statistics behind a specific trend — with full citations and publisher attribution. Each item includes source URL, location, brand names, publication date, category, and a formatted citation. Use a Inputs: graphId, for_node_id, userId, top_k |
get_label_values | List all brands, locations, technologies, audiences, or trends within a specific knowledge graph. Use to explore what a graph contains — e.g., "what brands are in the retail graph?" or "what locations does the fashion graph cover?". To get Inputs: graphId, label, userId, property |
get_my_account | Check the current user's account status: API call balance, plan, enabled/disabled graphs, and profile info. Use when the user asks "how many API calls do I have?", "what plan am I on?", "what graphs can I access?", or similar account questi |
get_neighbors | Discover what's connected to a specific trend — related brands, technologies, locations, and cross-domain links that search alone wouldn't surface. Returns curated editorial connections between trends that web search cannot provide. Use aft Inputs: graphId, seed_node_ids, userId, relationship_types, direction, depth |
get_node | Get the full profile of a specific trend — detailed description, lifecycle stage (emerging/building/mature), signal strength, geographic scope, and all properties. Use when you need deeper detail on a single trend after search_graph returne Inputs: graphId, nodeId, userId |
get_validated_trends | Returns market-validated consumer trends from corporate earnings reports cross-validated by Fodda's analysis pipeline. Connects earnings commentary (analyst concerns, CEO statements) with consumer trend signals. Inputs: ticker, sector, search, limit, userId |
list_graphs | List all expert knowledge graphs the user can access — IDs, descriptions, authors, sectors, signal counts, and topic coverage (e.g. retail, tech, food, travel, fashion, beauty, sports). Use FIRST in any session to discover available sources Inputs: userId |
search_graph | Find trends, signals, and expert insights across 100+ curated knowledge graphs covering retail, beauty, tech, food, travel, sports, and 30+ specialist domains. Returns trend data with cited evidence, source attribution, and lifecycle stage Inputs: mode, graphs, graphId, query, userId, limit |
Every block below points at https://mcp.fodda.ai/earnings-intelligence. Pick your client and copy.
claude mcp add --transport http fodda-earnings-intelligence https://mcp.fodda.ai/earnings-intelligence
{
"mcpServers": {
"fodda-earnings-intelligence": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://mcp.fodda.ai/earnings-intelligence"]
}
}
}{
"mcpServers": {
"fodda-earnings-intelligence": {
"url": "https://mcp.fodda.ai/earnings-intelligence"
}
}
}{
"servers": {
"fodda-earnings-intelligence": {
"type": "http",
"url": "https://mcp.fodda.ai/earnings-intelligence"
}
}
}{
"context_servers": {
"fodda-earnings-intelligence": {
"url": "https://mcp.fodda.ai/earnings-intelligence"
}
}
}{
"mcpServers": {
"fodda-earnings-intelligence": {
"serverUrl": "https://mcp.fodda.ai/earnings-intelligence"
}
}
}{
"mcpServers": {
"fodda-earnings-intelligence": {
"url": "https://mcp.fodda.ai/earnings-intelligence"
}
}
}name: Fodda Earnings Intelligence
version: 0.0.1
schema: v1
mcpServers:
- name: Fodda Earnings Intelligence
type: streamable-http
url: https://mcp.fodda.ai/earnings-intelligence{
"mcpServers": {
"fodda-earnings-intelligence": {
"httpUrl": "https://mcp.fodda.ai/earnings-intelligence"
}
}
}{
"mcpServers": {
"fodda-earnings-intelligence": {
"type": "http",
"url": "https://mcp.fodda.ai/earnings-intelligence"
}
}
}{
"mcpServers": {
"fodda-earnings-intelligence": {
"url": "https://mcp.fodda.ai/earnings-intelligence"
}
}
}goose://extension?url=https%3A%2F%2Fmcp.fodda.ai%2Fearnings-intelligence&type=streamable_http&id=fodda-earnings-intelligence&name=Fodda%20Earnings%20Intelligence
It answered our last check on 17 October 2026 in 181 ms. Over 10 checks since 4 September 2026 it answered 10. Status here comes from Neuronto's own probes, not from the publisher.
Yes. It is published by fodda.ai and served from mcp.fodda.ai, the vendor's own domain: https://mcp.fodda.ai/earnings-intelligence.
13, as returned by the server's own tools/list on 7 September 2026: generate_visual, get_capabilities, get_company_earnings, get_earnings_divergence, get_earnings_intelligence, get_evidence, get_label_values, get_my_account, and 5 more.
It answered our last check on 17 October 2026 in 181 ms. Over 10 checks since 4 September 2026 it answered 10.
Put the server under mcpServers in ~/.cursor/mcp.json with the URL https://mcp.fodda.ai/earnings-intelligence. The exact JSON is above, with the same setup for Claude Code, Claude Desktop, VS Code, Windsurf, Zed, Gemini CLI and the rest.
It needs a sign-in rather than a key you paste: the server answered with an authentication challenge, so your client runs the login when it first connects.
Publisher: ai.fodda. Endpoint host: mcp.fodda.ai. ARD identifier: urn:air:ai.fodda:mcp:earnings-intelligence.
First indexed 31 August 2026. The tools are exactly what the server returned; nothing on this page
is inferred from its name. Ranking in Neuronto search is never for sale.