Fodda Synthetic Expert Consult MCP Server

Use when seeking role-specific strategic guidance, executive decision frameworks, or historical perspectives from synthetic domain analysts, corporate C-Suite executive personas, or classic historical thinkers grounded in specialist knowledge graphs (e.g., 'Ask the Brand CMO persona how to evaluate retail media ROI', 'Consult John Ruskin on craftsmanship in luxury fashion'). Supports multi-turn dialogue via session_id, corporate brand binding via company, and comprehensive deep research (deep: true). Sibling routing: Use consult_human_agent for authorized Human Agents (Human Agents) (e.g. Ben Dietz); use consult_analyst for synthetic personas, C-Suite roles, and classic thinkers; use list_analysts to browse available personas. Returns synthesized analyst response, cited graph insights, and recommended next moves.

Use when consulting an authorized Human Agent (Digital Twin) — an AI expert model created directly with the named practitioner's consent, participation, and curated knowledge graph. The AI expert model answers in the practitioner's voice and analytical methodology for one-off questions or multi-turn engagements (pass session_id back to continue). Call find_expert or list_analysts first to find the right expert ID and distinguish active Human Agents (consultable immediately via consult_human_agent) from On-Request Human Agents (prospective advisors where introductions can be requested via request_expert_intro). Sibling routing: Use consult_human_agent for interactive AI consultation with active Human Agents; use consult_analyst for synthetic/classic personas. Returns practitioner-grounded analysis, coverage status (in/adjacent/out), source attribution, and structured next moves.

Use when commissioning an executive document from an analyst or Human Agent—such as a strategic briefing, market memo, competitive assessment, or publication-ready article—rather than conversational chat (e.g., 'Have Ben Dietz write a strategic memo on retail media networks'). Workflow routing: Discover available analysts and their specific commissionable offerings first via list_analysts or consult them interactively via consult_human_agent / consult_analyst. Execution & follow-up: Requests may process asynchronously; returns a job_id that can be polled to completion using check_deliverable_status. Returns job confirmation, estimated completion time, and deliverable status.

Use when a user wants to request a facilitated advisory introduction or 1-on-1 consultation with an On-Request Human Agent or active specialist across 4,150+ indexed topics, or when an expert does not maintain a direct public calendar link (e.g., 'I want to speak with Peter Abraham about bicycle retail strategy'). Sibling routing: Use consult_human_agent for immediate AI-driven consultation with active Human Agents; use find_expert to discover specialists; use request_expert_intro when the user seeks a human-to-human advisory introduction. Returns immediate request confirmation, concierge tracking reference, and expected email follow-up timeline.

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 questions. Returns live data — not cached from session start. (User account status & credit balance lookup.)

Catalog and discover all expert personas available on Fodda across 4 categories: living Human Agents (practitioners with Human Agent models), C-Suite Agents (corporate executive lenses grounded in earnings), Classic Agents (historical thinkers), and Synthetic Analysts (domain specialists). Use when exploring available experts, finding who to consult for a specific topic, or inspecting available specialist deliverables. Sibling routing: This tool lists and filters agents; to initiate an interactive conversation with a chosen specialist, call consult_human_agent (for living experts) or consult_analyst (for synthetic/classic/C-suite personas); to search experts by query match, use find_expert. Returns an array of agent profiles with analyst_id, canonical_slug, name, role, agent_class, topics, consult_tool, and commissionable offerings.

Returns Fodda's capabilities, semantic research workflows, Human Agents (Human Agents), and pricing. Call this for any question about what Fodda can do, how experts work, available research recipes, or pricing. Sibling routing: Use get_capabilities to discover platform features and workflow recipes; use list_graphs to list specific data graphs; use list_analysts to discover expert personas. Returns platform overview, active specialist counts, workflow descriptions, and published offerings.

Poll a deliverable commissioned with request_deliverable. Pass the job_id from that response. Returns the current status ("working" | "completed" | "failed") and, once completed, the artifact links to present to the user. Polling is free. Deliverables typically take a few minutes — poll every ~15–30s. (Expert deliverable job status poll.)

Evidence citation lookup: retrieves primary evidence articles, publisher case studies, data points, and source URLs that validate a specific trend node. Prerequisite: Requires a valid for_node_id and graphId obtained from a prior search_graph or get_neighbors call. Use when backing a specific trend with original reporting, verifying publisher citations, or extracting concrete brand examples. Sibling routing: Use search_graph first to discover trends and retrieve their node_id; use get_evidence to inspect the underlying source citations for that node; use get_node for high-level metadata; use search_statistics for standalone numbers. Returns an array of evidence items with title, publication, publication_date, snippet, and source_url.

Use when seeking candidate AI-powered Human Agent (Digital Twin) expert models or Synthetic Analysts across specialized domains or research questions (e.g. 'Who has expertise in luxury retail?' or 'What would consumer culture analysts say about this?'). Searches Fodda's catalog of 4,000+ domain specialists to return 2–3 ranked expert models with their analytical focus, methodology, credibility anchors, and expert ID for consultation via consult_human_agent or consult_analyst.

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_ladder" (Signal→Trend→So What→Do What), "innovation_pathway" (Now→Near-Term→Future), "opportunity_map" (2×2 white space analysis). Returns a branded SVG that renders directly in the chat. (Data payload transformation + SVG chart rendering.)

Use when searching for market trends, category dynamics, and consumer shifts across 100+ curated knowledge graphs. Returns trends with cited evidence, lifecycle stage (emerging/building/mature), and structured next_moves. Sibling routing: Use search_graph as the default starting tool for broad trend discovery; use search_statistics if you specifically need numerical data points and growth rates; use search_insights if you only need qualitative quotes and expert commentary; use brand_tracker if querying a specific company or brand name.

Catalog and discovery layer for Fodda knowledge graphs: lists all accessible knowledge graph IDs, topic vertical tags, author credentials, node counts, and signal metrics. Use first when discovering available domain libraries or when you need a valid graphId parameter for graph-scoped queries (e.g. "What knowledge graphs do you have on retail or sustainability?"). Sibling routing: Use list_graphs to inspect graph metadata and available sources; use search_graph to query trend content across graphs; use list_analysts to discover specialist Human Agents. Returns an array of graph profiles with graphId, name, topics, signal_count, and author.

List unique taxonomy entity values (brands, locations, technologies, audiences) or retrieve the complete table of contents for small, discrete report graphs (<40 trends, e.g. DHL, PwC, or Mintel radars) where search may return partial results. Returns up to 100 unique values ordered alphabetically. Sibling routing: DO NOT use this tool for thematic or topic research (e.g. 'find AI trends' or 'what trends are in tech?') on large domain graphs (tech, retail, cpg), because it caps at 100 items alphabetically without evidence or signals; use search_graph instead for semantic trend retrieval. (Graph taxonomy label value lookup.)

Discover what's connected to a specific trend — related brands, technologies, locations, and cross-domain links. Returns curated editorial connections between trends. Use after search_graph to map the territory around a trend, find which brands are connected, or understand cross-domain relationships. Requires node_id from a prior search_graph result. (1-hop graph relationship traversal from seed node in Neo4j.)

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 returned a summary. Requires node_id from a prior search_graph result. (Direct Neo4j node metadata lookup by ID.)

Use when verifying a factual claim, hypothesis, or strategic assertion against a named practitioner's curated knowledge graph via their AI-powered Human Agent (Digital Twin) model. Evaluates whether the practitioner's documented research and domain evidence supports or refutes the claim. If analyst_id is omitted, automatically routes to the most relevant active Human Agent covering the domain. Sibling routing: Use verify_claim to evaluate a claim against a specific practitioner's knowledge graph and receive a structured verdict; use verify_market_claim for multi-graph algorithmic 5-gate verification across 100+ graphs and earnings. Returns a structured verification object with verdict ("confirms", "contradicts", "partial", or "no_coverage"), confidence ("full", "partial", or "thin"), one_line summary, rationale, cited sources, and expert attribution.