Fodda Deep Research
REMOTE · MCP.FODDA.AI · SCANNED OCT 4
Autonomous deep research reports merging PSFK trend graphs with citable sources.
Available components
How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. How we score → Why this is hard to score →
Endpoint Security89
- The endpoint's TLS certificate is valid, in date, and uses a strong key. View diagnostics → Pass
- The endpoint enforces authorisation, advertised via RFC 9728 protected-resource metadata. View diagnostics → Pass
- HTTPS is enforced; there's no plaintext access path. View diagnostics → Pass
- HSTS check failed: the Strict-Transport-Security header is absent. See how to fix → View diagnostics → Fail
- DNSSEC check failed: this domain isn't protected by DNSSEC. See how to fix → View diagnostics → Fail
- The authorisation server offers only Dynamic Client Registration (RFC 7591), which MCP 2026-07-28 deprecated in favour of Client ID Metadata Documents. View diagnostics → Partial
Transport & Reachability0
- Transport blocked by authentication: the endpoint requires auth we don't have to verify streamable-http. See how to fix → View diagnostics → Unverified
Schema Quality & AI Usability0
- Schema blocked by authentication: the endpoint requires auth we don't have to read it. See how to fix → Unverified
Stability & Change Management0
- Stability not yet verified: not enough scan history yet (needs a 30-day window).Unverified
Tool Coverage0
- Tool coverage blocked by authentication: the endpoint requires auth we don't have to read its tools.Unverified
Tool Safety0
- Tool safety blocked by authentication: the endpoint requires auth we don't have to read its tools.Unverified
Capabilities0
- Capabilities blocked by authentication: the endpoint requires auth we don't have to read them. See how to fix → Unverified
Unverified: 6 categories
Categories scored 0 because we could not verify them: authentication we do not have, an unreachable endpoint, or not enough scan history. We only credit what we can confirm. Claim this server and supply a read-only token to verify it and lift the score.
How do I install the Fodda Deep Research MCP server?
Fodda Deep Research is a hosted endpoint at https://mcp.fodda.ai/deep-research, so there is nothing to install locally. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
remote · mcp.fodda.ai
claude mcp add --transport http ai-fodda-deep-research 'https://mcp.fodda.ai/deep-research'
{
"mcpServers": {
"ai-fodda-deep-research": {
"url": "https://mcp.fodda.ai/deep-research"
}
}
} {
"servers": {
"ai-fodda-deep-research": {
"type": "http",
"url": "https://mcp.fodda.ai/deep-research"
}
}
} [mcp_servers.ai-fodda-deep-research] url = "https://mcp.fodda.ai/deep-research"
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"ai-fodda-deep-research": {
"type": "remote",
"url": "https://mcp.fodda.ai/deep-research",
"enabled": true
}
}
} openclaw mcp add ai-fodda-deep-research --url 'https://mcp.fodda.ai/deep-research' --transport streamable-http
mcp_servers:
ai-fodda-deep-research:
url: "https://mcp.fodda.ai/deep-research" {
"McpServers": {
"ai-fodda-deep-research": {
"Transport": "http",
"Url": "https://mcp.fodda.ai/deep-research"
}
}
} assistant mcp add ai-fodda-deep-research -t streamable-http -u 'https://mcp.fodda.ai/deep-research'
{
"mcpServers": {
"ai-fodda-deep-research": {
"type": "http",
"url": "https://mcp.fodda.ai/deep-research"
}
}
} The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.
Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 28 Sept 26 0
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
- 25 Sept 26 0
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
- 3 Sept 26 0
- Endpoint reachability: reachable → behind authorisation ▼ security
- Stability: pass → unverified ▼ security
- Tool safety: pass → unverified ▼ security
- Transport: fail → unverified ▼ security
- Authorization: partial → pass ▲ security
- First check of Authorization: partial security
- Capabilities: pass → unverified ▼ functional
- Tool coverage: 100 → unverified ▼ functional
- Schema quality: 100 → unverified ▼ functional
- 2 Sept 26 0
- The server rewrote its instructions, which are the text every model session reads security
- Tool “generate_visual” rewrote its description, which is the text the model reads security
- Server version: 1.46.40 → 1.46.48 functional
- “generate_visual” reworded the description of “data” cosmetic
- 1 Sept 26 0
- The server rewrote its instructions, which are the text every model session reads security
- 31 Aug 26 0
- The server rewrote its instructions, which are the text every model session reads security
- 29 Aug 26 0
- The server rewrote its instructions, which are the text every model session reads security
- Server version: 1.46.39 → 1.46.40 functional
- 28 Aug 26 0
- The server rewrote its instructions, which are the text every model session reads security
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 4 Oct 2026 · Probed https://mcp.fodda.ai/deep-research
TLS valid
Negotiated TLS 1.3 with TLS_AES_128_GCM_SHA256 .
| Subject | Issuer | Valid from | Valid until | Key | Signature | Serial |
|---|---|---|---|---|---|---|
| CN=mcp.fodda.ai | CN=WR3,O=Google Trust Services,C=US | 19 Sept 2026 | 18 Dec 2026 | RSA 2048 | SHA256-RSA | 743b8391516e76fb1071db45b32cf2b6 |
| SANs: mcp.fodda.ai | ||||||
| CN=WR3,O=Google Trust Services,C=US (CA) | CN=GTS Root R1,O=Google Trust Services LLC,C=US | 13 Dec 2023 | 20 Feb 2029 | RSA 2048 | SHA256-RSA | 7ff005a91568d63abc22861684aa4b5a |
| CN=GTS Root R1,O=Google Trust Services LLC,C=US (CA) | CN=GlobalSign Root CA,OU=Root CA,O=GlobalSign nv-sa,C=BE | 19 Jun 2020 | 28 Jan 2028 | RSA 4096 | SHA256-RSA | 77bd0d6cdb36f91aea210fc4f058d30d |
Background: What to check on a remote MCP endpoint →
DNSSEC insecure
Validation of mcp.fodda.ai. — Not signed
| Zone | DS | Keys | Algorithms | Outcome |
|---|---|---|---|---|
| . | trust_anchor | 20326, 38696 | 8, 8 | Verified |
| ai. | present | 3799 | 8 | Verified |
| fodda.ai. | absent | Unsigned (proven) parent-signed NSEC/NSEC3 proves an unsigned delegation |
Authentication Enforced and verified
The endpoint asked for a token and published valid RFC 9728 metadata describing how to get one.
| Result | Enforced and verified |
|---|---|
| Enforced | On connection |
| HTTP status | 401 |
WWW-Authenticate challenge Bearer resource_metadata="https://mcp.fodda.ai/.well-known/oauth-protected-resource/deep-research"
Bearer resource_metadata="https://mcp.fodda.ai/.well-known/oauth-protected-resource/deep-research" | Header | Value |
|---|---|
| www-authenticate | Bearer resource_metadata="https://mcp.fodda.ai/.well-known/oauth-protected-resource/deep-research" |
Protected resource metadata
| Document | https://mcp.fodda.ai/.well-known/oauth-protected-resource/deep-research |
|---|---|
| Retrieved | Yes |
| Resource | https://mcp.fodda.ai/deep-research |
| Authorisation server | https://clerk.fodda.ai |
Background: How OAuth 2.1 works in the 2026 MCP spec →
Transports 2 probes
| Transport | URL | Outcome | Status | Location |
|---|---|---|---|---|
| streamable-http | https://mcp.fodda.ai/deep-research | Auth required | 401 | |
| http (plaintext) | http://mcp.fodda.ai/deep-research | HTTPS enforced | 302 | https://mcp.fodda.ai/deep-research |
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →
check_research_status ~59
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.
| Name | Type | Req | Description |
|---|---|---|---|
| job_id | string | yes | The Job ID returned by deep_research_topic |
No output schema declared.
No examples provided.
check_supplemental_status ~67
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 or FAILED.
| Name | Type | Req | Description |
|---|---|---|---|
| job_id | string | yes | The Job ID returned by get_supplemental_context |
No output schema declared.
No examples provided.
deep_research_topic ~339
Launch an autonomous Deep Research session that combines Fodda knowledge graph intelligence with live web research to produce a comprehensive editorial-quality report. The Research Agent plans its own strategy, searches multiple graphs, validates with institutional data, and synthesizes into a narrative brief with inline source citations. Use for complex, multi-faceted questions that need both curated expert intelligence AND current web context — e.g., strategic briefings, market landscape reports, competitive deep dives. Automatically includes earnings-call intelligence and macro/supplemental data when the topic warrants it (public companies, sectors, economic conditions). You do not need to call the earnings or supplemental tools separately before or after.
| Name | Type | Req | Description |
|---|---|---|---|
| depth | string | – | Research depth: "light" for faster research, "heavy" for comprehensive deep dive. Defaults to "light". |
| graphId | string | – | Optional specific graph ID to limit the research to |
| mode | string | – | Research mode: "light" for faster research, "heavy" for comprehensive deep dive. Defaults to "light". |
| query | string | yes | The research subject as a short phrase, 5–15 words. Do not pass a full brief — long multi-clause queries degrade graph selection. Put detail into sub_themes instead. |
| sub_themes | array | – | 3–5 specific angles to investigate (e.g. "category sizing and growth forecasts for wine coolers", "key players across appliance, furniture and glassware", "DTC versus wholesale channel dynamics"). If… |
| userId | string | – | Optional user identifier. |
No output schema declared.
No examples provided.
generate_visual ~312
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. Highlight focal entity using top-level "focus":"Name" or per-item "focus":true.
| Name | Type | Req | Description |
|---|---|---|---|
| chart_type | string | yes | The type of visualization to generate |
| data | string | yes | JSON string containing chart data. Optional top-level "focus":"Name" or per-item "focus":true highlights key entity in brand accent. cultural_shifts: {shifts:[{from,to}]}. competitive_compass: {brand… |
No output schema declared.
No examples provided.
get_capabilities ~59
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.
| Name | Type | Req | Description |
|---|---|---|---|
| userId | string | – | Optional user identifier. |
No output schema declared.
No examples provided.
get_evidence ~318
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 after search_graph when you need the supporting proof behind a trend. This is a direct lookup by trend ID — not a text search tool.
| Name | Type | Req | Description |
|---|---|---|---|
| for_node_id | string | yes | The node_id from a prior search_graph result (e.g. '2507.0'). MUST come from the search result's node_id field. Node IDs are NOT sequential integers — do NOT guess or invent IDs like '1', '2', '3'. D… |
| graphId | string | yes | The graph ID. Use list_graphs to see all options. Examples: 'retail', 'tech', 'food', 'travel', 'beauty', 'sports', 'sic', 'pew', 'ce-design', 'ezra-eeman-wayfinder', 'dhl-ecommerce-trends-2026', 'au… |
| top_k | number | – | Number of evidence items to return (default 5) |
| userId | string | – | Optional user identifier for trial usage tracking. |
No output schema declared.
No examples provided.
get_label_values ~300
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 a complete list of every trend in a graph, call with label="Trend" — this returns the full deterministic list, useful for industry-report graphs where search may return partial results.
| Name | Type | Req | Description |
|---|---|---|---|
| graphId | string | yes | The graph ID. Use list_graphs to see all options. Examples: 'retail', 'tech', 'food', 'travel', 'beauty', 'sports', 'sic', 'pew', 'ce-design', 'ezra-eeman-wayfinder', 'dhl-ecommerce-trends-2026', 'au… |
| label | string | yes | The label to fetch values for (e.g., 'Brand', 'Location', 'Technology', 'Audience', 'RetailerType', 'Trend') |
| property | string | – | Optional property to return values for. Defaults vary by label. |
| userId | string | – | Optional user identifier for trial usage tracking. |
No output schema declared.
No examples provided.
get_my_account ~74
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.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
get_neighbors ~409
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 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.
| Name | Type | Req | Description |
|---|---|---|---|
| depth | number | – | Traversal depth (default 1, max 2) |
| direction | string | – | Traversal direction: 'out' (default) follows outgoing edges, 'in' follows incoming edges |
| graphId | string | yes | The graph ID. Use list_graphs to see all options. Examples: 'retail', 'tech', 'food', 'travel', 'beauty', 'sports', 'sic', 'pew', 'ce-design', 'ezra-eeman-wayfinder', 'dhl-ecommerce-trends-2026', 'au… |
| limit | number | – | Maximum results (default 50) |
| relationship_types | array | – | Filter by relationship types: 'EVIDENCED_BY', 'RELATED_TO', 'SEMANTICALLY_SIMILAR', 'ASSOCIATED_BRAND', 'MENTIONS_BRAND', 'IN_LOCATION' |
| seed_node_ids | array | yes | Array of node IDs to start traversal from. MUST be actual node_id values from a prior search_graph result (e.g. ["2507.0"]). Node IDs are NOT sequential integers — do NOT guess or invent IDs like "1"… |
| userId | string | – | Optional user identifier for trial usage tracking. |
No output schema declared.
No examples provided.
get_node ~285
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.
| Name | Type | Req | Description |
|---|---|---|---|
| graphId | string | yes | The graph ID. Use list_graphs to see all options. Examples: 'retail', 'tech', 'food', 'travel', 'beauty', 'sports', 'sic', 'pew', 'ce-design', 'ezra-eeman-wayfinder', 'dhl-ecommerce-trends-2026', 'au… |
| nodeId | string | yes | The node_id from a prior search_graph result (e.g. '2507.0'). MUST come from the search result's node_id field. Node IDs are NOT sequential integers — do NOT guess or invent IDs like '1', '2', '3'. D… |
| userId | string | – | Optional user identifier for trial usage tracking. |
No output schema declared.
No examples provided.
get_supplemental_context ~341
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 demand/attention-shaped (e.g. to get search volume, economic series, or census data). It retrieves data from 80+ authoritative sources (Google Trends, FRED, BLS, Census, etc.) fanned out in parallel. Returns categorized data blocks with source attribution and metadata. Note: call after search_graph indicates thin/empty coverage via its coverage annotation.
| Name | Type | Req | Description |
|---|---|---|---|
| brands | array | – | Brand names to include in demand/product lookups (e.g., ['Nike', 'Adidas']). Triggers Google Trends comparison and Amazon product search. |
| domain | string | – | Domain hint to improve source routing: 'retail', 'beauty', 'fashion', 'sports', 'food', 'technology', 'culture', 'travel', 'design', 'macro'. Do NOT pass 'culture' or 'technology' for macro economic… |
| geo | string | – | Country code or geography hint (e.g., 'TH', 'US', 'GB') for country-filtered queries. |
| graph_ids | array | – | Graph IDs from prior search results — helps refine domain inference. |
| query | string | yes | The topic or query to get supplemental data for (e.g., 'sustainable packaging', 'tequila spirits market', 'Gen Z beauty'). Include country names if searching non-US markets (e.g. 'Thailand consumer s… |
| userId | string | – | Optional user identifier for trial usage tracking. |
No output schema declared.
No examples provided.
list_graphs ~105
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 before searching. Returns graph metadata needed for graphId parameters in other tools.
| Name | Type | Req | Description |
|---|---|---|---|
| userId | string | – | Optional user identifier. Authenticated users are identified automatically via API key. For trial users, this helps track usage. |
No output schema declared.
No examples provided.
read_url ~87
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-reference it against Fodda knowledge graphs. Returns structured text ready for analysis.
| Name | Type | Req | Description |
|---|---|---|---|
| url | string | yes | The URL to read and extract content from |
| userId | string | – | Optional user identifier for usage tracking. |
No output schema declared.
No examples provided.
search_graph ~512
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 (emerging/building/mature/fading) — not generic web summaries. If graphId is omitted, searches ALL accessible graphs in parallel (recommended default). Use for market trends, competitor analysis, innovation signals, consumer behavior, cultural shifts, or any topic where curated expert intelligence outperforms web search.
| Name | Type | Req | Description |
|---|---|---|---|
| graphId | string | – | Optional graph ID. If omitted, searches ALL accessible graphs. Examples: 'retail', 'tech', 'food', 'travel', 'beauty', 'sports', 'sic', 'pew', 'ce-design', 'ezra-eeman-wayfinder', 'dhl-ecommerce-tren… |
| graphs | array | – | Optional explicit graph scope: an array of graph IDs. When provided, the search is restricted to EXACTLY these graphs — no fallback routing to other graphs. Graph IDs that are unknown, not live, or n… |
| include_evidence | boolean | – | If true, batch-fetch supporting evidence articles inline with results. Default: true. |
| limit | number | – | Maximum number of results (default 10, max 50) |
| mode | string | – | Execution mode: "research" for topic research, "compare" for upload & compare intelligence. Defaults to "research". |
| query | string | yes | The search query. Country/regional terms filter results at the macro level. Note: Knowledge graph trends are indexed at country/global scope — for sub-national or city-level data (e.g., "US coastal c… |
| skip_skills | boolean | – | If true, skip applying any enabled search enhancement skills for this query only. Use when you want raw, un-enhanced graph results. Default: false. |
| use_semantic | boolean | – | Whether to use semantic search (default true) |
| userId | string | – | Optional user identifier for trial usage tracking. |
No output schema declared.
No examples provided.
What is the Fodda Deep Research MCP server?
Fodda Deep Research is an MCP server listed in the public MCP registry as ai.fodda/deep-research. Autonomous deep research reports merging PSFK trend graphs with citable sources. This page covers its hosted endpoint (https://mcp.fodda.ai/deep-research).
Is the Fodda Deep Research MCP server safe to use?
Fodda Deep Research scores 36 out of 100 on VerifyMCP. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.
What tools does the Fodda Deep Research MCP server expose?
Fodda Deep Research exposes 14 tools: get_my_account, list_graphs, get_capabilities, search_graph, get_neighbors, and 9 more. Their descriptions and schemas cost roughly 3,267 tokens of context every time the server is loaded.
Does the Fodda Deep Research MCP server require authentication?
Yes. Fodda Deep Research asked us for credentials when we connected, so you will need to authorise it in your MCP client before it can do anything.
Is the Fodda Deep Research MCP server still maintained?
Fodda Deep Research is still listed as active in the MCP registry. We last reached this channel on 4 October 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.