# Fodda MCP server

Source: https://glimind.com/server/mcp-registry%2Fai.fodda%2Fmcp-server
Registry id: `mcp-registry/ai.fodda/mcp-server`
Status: auth-required (checked 2026-10-26T19:44:47.356Z)

## Measurements (30 days)

- Uptime: 100%
- Checks: 212
- Outages (90 days): 13

## Install

```json
{
  "mcpServers": {
    "fodda-mcp-server": {
      "type": "http",
      "url": "https://mcp.fodda.ai/mcp"
    }
  }
}
```

Claude Code:

```sh
claude mcp add --transport http fodda-mcp-server https://mcp.fodda.ai/mcp
```

## Tools (46)

- `begin_expert_onboarding`: Begin the Fodda expert onboarding process. Instruct the agent/LLM to manage expectations immediately. When asking the expert for their topic focus first and the
- `brainstorm_topic`: Explore and brainstorm around a topic using knowledge graph connections. Unlike search (which finds what matches), this tool discovers what CONNECTS — adjacent 
- `brand_tracker`: Build a complete Brand Intelligence Profile by searching ALL knowledge graphs for a specific brand. Returns trend footprint (which trends the brand appears in),
- `check_deliverable_status`: Poll a deliverable commissioned with request_deliverable. Pass the job_id from that response. Returns the current status ("working" | "completed" | "failed") an
- `check_research_status`: Check if deep research is complete and retrieve the final report. Call this after deep_research_topic — poll every 10 seconds until status is COMPLETE or FAILED
- `check_supplemental_status`: Check if market data gathering is complete and retrieve the results. Call this after get_supplemental_context — poll every 5-10 seconds until status is COMPLETE
- `confirm_themes`: Confirm the selected themes to generate the interview questionnaire. Instruct the agent/LLM that when themes/topics are confirmed/returned, it must reframe the 
- `consult_analyst`: Consult a named Synthetic Analyst who answers in their expert voice using their curated knowledge graph — one-off questions or multi-turn engagements (pass sess
- `deep_research_topic`: Launch an autonomous Deep Research session that combines Fodda knowledge graph intelligence with live web research to produce a comprehensive editorial-quality 
- `discover_adjacent_trends`: Find trends similar to one you've already found — surfaces unexpected cross-domain connections that keyword search would miss. Returns scored similarity matches
- `draft_linkedin_article`: Turn research into a LinkedIn ARTICLE (800–1,200 words) grounded in Fodda's expert knowledge graphs. Use when the user says "turn this research into an article…
- `draft_linkedin_post`: Draft a LinkedIn post about any topic, grounded in Fodda's expert knowledge graphs. Use when the user says "draft a LinkedIn post about…", "write a post on…", "
- `expert_onboarding_research`: Kick off asynchronous background research on your public work for the expert onboarding. The identity is derived from your connector session.
- `generate_visual`: Create a presentation-ready data visualization from research findings. Available chart types: "cultural_shifts" (From→To transitions), "competitive_compass" (br
- `get_capabilities`: Returns Fodda's main capabilities / features / offerings / products / services / tools and what they cost. Call this for any question about what Fodda can do or
- `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 
- `get_detected_themes`: Fetch the detected themes derived from the expertise analysis and background research. Instruct the agent/LLM that when themes come back, it must reframe the in
- `get_domain_intelligence`: Search PSFK-curated domain graphs (retail, beauty, fashion, sports, consumer electronics, F&B) for trend intelligence with bundled evidence. No graph ID needed 
- `get_earnings_divergence`: Cross-company analyst-management divergence detection from the knowledge graph (legacy-thematic). Surfaces where executives are deflecting, reframing, or avoidi
- `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
- `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, lo
- `get_expert_intelligence`: Search specialist knowledge graphs built by named strategists and industry leaders — contains proprietary analysis, expert interviews, and high-density statisti
- `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 
- `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
- `get_my_earnings`: Check the expert's Fodda earnings.
- `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 cura
- `get_node`: Get the full profile of a specific trend — detailed description, lifecycle stage (emerging/building/mature), signal strength, geographic scope, and all properti
- `get_onboarding_status`: Check the status of the expert onboarding process. The identity is derived from your connector session. IMPORTANT: analystId is an internal reference — do not d
- `get_report_intelligence`: Search industry report knowledge graphs for published research findings, market forecasts, and quantitative projections from organizations like DHL, PwC, Delta,
- `get_supplemental_context`: A standard layer for macro, institutional, and real-time market data. Call this tool when curated coverage is thin, empty, or when the query is explicitly deman
- `get_validated_trends`: Returns market-validated consumer trends from corporate earnings reports cross-validated by Fodda's analysis pipeline. Connects earnings commentary (analyst con
- `list_analysts`: Lists available synthetic analyst personas (e.g. brand-cmo, brand-ceo, brand-cfo). To query a company-specific synthetic expert (e.g., "Nike CMO", "Apple CMO", 
- `list_graphs`: List all knowledge graphs the user can access — IDs, descriptions, authors, sectors, signal counts. Use FIRST in any session to discover available sources befor
- `manage_scheduled_reports`: Create, list, cancel, update, pause, or resume scheduled intelligence briefings. Users can set up autonomous research that runs weekly (Mondays) or daily (Mon-F
- `read_url`: Extract clean text content from any URL. Use this when a user shares a link (competitor site, news article, client brief, trend report) and wants to cross-refer
- `request_deliverable`: Commission a finished document from an analyst — a skill-based deliverable like a marketing plan, deck review, or trend briefing. Specify offering_key (see the 
- `schedule_interview`: Schedule your voice interview. You can specify a datetime (UTC ISO string) and localTimeStr (human-readable time, e.g. "Tuesday, July 14 at 3:00 PM EDT"), or re
- `search_graph`: Find trends, signals, and expert insights across 100+ curated knowledge graphs covering retail, beauty, tech, food, travel, sports, and 30+ specialist domains. 
- `search_insights`: NARRATIVE only: expert quotes, editorial analysis, and strategic perspectives on a topic — sourced from named strategists and industry leaders. Returns qualitat
- `search_statistics`: HARD NUMBERS only: specific figures, market sizes, growth rates, and quantitative data points across Fodda's knowledge graphs. Each result links back to the exp
- `send_feedback`: Forward user feedback, feature requests, complaints, or exit reasons to the Fodda team via email and Slack. Call this whenever a user shares feedback — includin
- `sign_up_free_account`: Create a free Fodda Base account (100 API calls/month across ALL knowledge graphs) and send a confirmation email. GUARDRAIL: only call this AFTER the user has e
- `submit_basic_info`: Submit basic information (name, role, knowledge area) for the expert onboarding process. IMPORTANT: analystId is an internal reference — do not display it to th
- `submit_expertise_analysis`: Submit the analyzed voice study and expertise map JSON outputs from the LLM. Once submitted, the next steps in the chain are to call get_detected_themes, then c
- `toggle_graph_preference`: Enable or disable any knowledge graph, supplemental data source, or skill for the user. Use this when the user says "Turn off Paralogy", "Enable igloo", "Disabl
- `update_user_profile`: Save the user's research profile to improve the relevance of future responses. Call this after you understand the user's role, industry, and research needs. The

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