Combien d'outils expose io.github.MCFLAMINGO/local-intel ?

io.github.MCFLAMINGO/local-intel expose 27 outil(s). Le coût de contexte pour les charger tous est d'environ 4925 tokens (coût unique au chargement, pas par appel).

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io.github.MCFLAMINGO/local-intel

serveur MCP (Model Context Protocol) · localintel 1.0.0

▸ Géo & Temps

[ Non encore testé ]

Verdict MCP Hub
Référencé dans l'annuaire. Seul le pentest comportemental fait foi, et il n'a pas encore été exécuté sur ce serveur.

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~4925 tokensCoût de contexte

27Outils

Est-ce que io.github.MCFLAMINGO/local-intel est sûr ?

Au dernier audit MCP Hub, le serveur MCP « io.github.MCFLAMINGO/local-intel » est classé « Non encore testé ». Référencé dans l'annuaire. Seul le pentest comportemental fait foi, et il n'a pas encore été exécuté sur ce serveur. Le verdict est réévalué en continu ; consultez la fiche pour l'état à jour.

Méthode : MCP Hub analyse la description de chaque outil (couche 1) et, pour le verdict fort, exécute le serveur dans une micro-VM isolée avec leurres et réseau bloqué (couche 2). On publie des noms et des compteurs, jamais le contenu brut renvoyé par un outil.

Les 27 outils

local_intel_ask≈ 204 tokens
Composite NL query layer. Ask any plain-English question about a ZIP — demographics, market opportunity, restaurant gaps, retail saturation, construction activity, investment signals, healthcare, corridor analysis, recent changes, nearby businesses. Routes internally to the right tools and returns a synthesized, sourced answer with confidence score. Best single entry point for humans and LLMs.
Paramètres, retour & exemple (2)
Paramètres
- zip · string · optionnel
  ZIP code (optional — will be extracted from question if present, defaults to 32082)
- question · string · requis
  Plain English question, e.g. "What restaurant categories are missing in 32082?"
Exemple d'appel
```
{"name": "local_intel_ask", "arguments": {"question": "texte"}}
```
Exemple de retour
```
{"content": [{"type": "text", "text": "…"}]}
```
local_intel_bedrock≈ 137 tokens
Infrastructure momentum score and active leading indicators for a ZIP from Layer 0. Permits, road projects, flood zones, utility extensions. Predicts conditions 12-36 months ahead. 'Let Google pay for the satellites — we sell the weather forecast.'
Paramètres, retour & exemple (2)
Paramètres
- zip · string · requis
  ZIP code
- query_context · object · optionnel
  Optional: { agent_type, agent_id }
Exemple d'appel
```
{"name": "local_intel_bedrock", "arguments": {"zip": "texte"}}
```
Exemple de retour
```
{"content": [{"type": "text", "text": "…"}]}
```
local_intel_book≈ 122 tokens
Book a specific response to an RFQ — confirms the job with that business. Use after reviewing local_intel_rfq_status responses.
Paramètres, retour & exemple (3)
Paramètres
- note · string · optionnel
  Optional note to the business
- rfq_id · string · requis
  UUID of the RFQ
- response_id · string · requis
  UUID of the response to accept
Exemple d'appel
```
{"name": "local_intel_book", "arguments": {"rfq_id": "texte", "response_id": "texte"}}
```
Exemple de retour
```
{"content": [{"type": "text", "text": "…"}]}
```
local_intel_changes≈ 92 tokens
Recently added or owner-verified business listings. Use to detect new openings or data updates.
Paramètres, retour & exemple (2)
Paramètres
- zip · string · optionnel
  Optional ZIP filter
- limit · integer · optionnel
  Max results (default 20)
Exemple d'appel
```
{"name": "local_intel_changes", "arguments": {"zip": "texte", "limit": 1}}
```
Exemple de retour
```
{"content": [{"type": "text", "text": "…"}]}
```
local_intel_compare≈ 211 tokens
Compare up to 10 ZIP codes side-by-side and get a ranked opportunity table. Returns per-ZIP signals (HHI, capture rate, infra momentum, consumer profile, top gap) plus a top_pick recommendation with reasoning. Best tool for site selection, franchise expansion, investment screening, and market prioritization.
Paramètres, retour & exemple (3)
Paramètres
- zips · array · requis
  Array of ZIP codes to compare, e.g. ["32082","32081","32084"]. Max 10.
- focus · string · optionnel
  Ranking focus: "opportunity" (default), "hhi", "saturation", "growth", or "population".
- limit · number · optionnel
  Max rows to return (default 10).
Exemple d'appel
```
{"name": "local_intel_compare", "arguments": {"zips": []}}
```
Exemple de retour
```
{"content": [{"type": "text", "text": "…"}]}
```
local_intel_complete≈ 118 tokens
Mark a booked job as complete and settle payment to the local merchant wallet (Tempo pathUSD when SETTLEMENT_ENABLED=true; otherwise records settled_intent and feeds the forecast loop).
Paramètres, retour & exemple (2)
Paramètres
- note · string · optionnel
  Completion note or rating
- booking_id · string · requis
  UUID returned by local_intel_book
Exemple d'appel
```
{"name": "local_intel_complete", "arguments": {"booking_id": "texte"}}
```
Exemple de retour
```
{"content": [{"type": "text", "text": "…"}]}
```
local_intel_construction≈ 183 tokens
Construction and home services market intelligence for a ZIP. Ask about contractor density, active permits, housing starts, population growth driving demand. Returns structured data with confidence score. Trained on 100 construction business prompts.
Paramètres, retour & exemple (4)
Paramètres
- lat · number · optionnel
  Latitude (WGS84) — resolves to nearest FL ZIP
- lon · number · optionnel
  Longitude (WGS84)
- zip · string · optionnel
  ZIP code to analyze
- query · string · requis
  Natural language question about construction market
Exemple d'appel
```
{"name": "local_intel_construction", "arguments": {"query": "texte"}}
```
Exemple de retour
```
{"content": [{"type": "text", "text": "…"}]}
```
local_intel_context≈ 178 tokens
Full spatial context block for any FL zip or lat/lon. Returns anchor business, nearby businesses in distance rings, zone intelligence, and category breakdown. Best first call for any location query. Covers all 1,473 FL ZIPs via fl_zip_geo.
Paramètres, retour & exemple (4)
Paramètres
- lat · number · optionnel
  Latitude (WGS84) — resolves to nearest FL ZIP
- lon · number · optionnel
  Longitude (WGS84) — required if lat is provided
- zip · string · optionnel
  Any FL ZIP code
- radius_miles · number · optionnel
  Search radius in miles (default 1.0)
Exemple d'appel
```
{"name": "local_intel_context", "arguments": {"lat": 1, "lon": 1, "zip": "texte", "radius_miles": 1}}
```
Exemple de retour
```
{"content": [{"type": "text", "text": "…"}]}
```
local_intel_corridor≈ 132 tokens
Businesses along a named street corridor. Use for queries like "what is on A1A" or "businesses on Palm Valley Road".
Paramètres, retour & exemple (3)
Paramètres
- zip · string · optionnel
  Optional ZIP filter
- limit · integer · optionnel
  Max results (default 20)
- street · string · requis
  Street name (e.g. "A1A", "Palm Valley", "Crosswater")
Exemple d'appel
```
{"name": "local_intel_corridor", "arguments": {"street": "texte"}}
```
Exemple de retour
```
{"content": [{"type": "text", "text": "…"}]}
```
local_intel_decline_response≈ 150 tokens
Decline a specific response to an RFQ and get the next in queue. Use when a client rejects the first responder — returns the next pending response automatically. First come first served queue.
Paramètres, retour & exemple (3)
Paramètres
- reason · string · optionnel
  Optional reason for declining (e.g. price too high, too far)
- rfq_id · string · requis
  UUID of the RFQ
- response_id · string · requis
  UUID of the response to decline
Exemple d'appel
```
{"name": "local_intel_decline_response", "arguments": {"rfq_id": "texte", "response_id": "texte"}}
```
Exemple de retour
```
{"content": [{"type": "text", "text": "…"}]}
```
local_intel_for_agent≈ 288 tokens
PREMIUM composite entry point ($0.05). Declare your agent_type and intent, receive pre-ranked top-10 signals assembled from all 4 data layers, personalized for your use case. Includes delta since your last query if agent_id provided. Best first call for any new agent.
Paramètres, retour & exemple (8)
Paramètres
- lat · number · optionnel
  Latitude (if no ZIP)
- lon · number · optionnel
  Longitude (if no ZIP)
- zip · string · optionnel
  Target ZIP code
- depth · string · optionnel
  quick (top 5 signals) | full (top 10 + context blocks)
- budget · number · optionnel
  Agent budget in pathUSD (optional, for signal prioritization)
- intent · string · optionnel
  Plain-language description of what you are trying to decide or do
- agent_id · string · optionnel
  Your agent UUID for memory + delta computation
- agent_type · string · optionnel
  real_estate | financial | ad_placement | logistics | business_owner | civic
Exemple d'appel
```
{"name": "local_intel_for_agent", "arguments": {"lat": 1, "lon": 1, "zip": "texte", "depth": "texte", "budget": 1, "intent": "texte"}}
```
Exemple de retour
```
{"content": [{"type": "text", "text": "…"}]}
```
local_intel_healthcare≈ 173 tokens
Healthcare market intelligence for a ZIP. Ask about provider density, patient demographics, demand gaps, senior population. Returns structured data with confidence score. Trained on 100 healthcare business prompts.
Paramètres, retour & exemple (4)
Paramètres
- lat · number · optionnel
  Latitude (WGS84) — resolves to nearest FL ZIP
- lon · number · optionnel
  Longitude (WGS84)
- zip · string · optionnel
  ZIP code to analyze
- query · string · requis
  Natural language question about healthcare market
Exemple d'appel
```
{"name": "local_intel_healthcare", "arguments": {"query": "texte"}}
```
Exemple de retour
```
{"content": [{"type": "text", "text": "…"}]}
```
local_intel_nearby≈ 177 tokens
Find businesses within a radius of any lat/lon point, sorted by distance with compass bearing.
Paramètres, retour & exemple (6)
Paramètres
- lat · number · requis
  Latitude of center point
- lon · number · requis
  Longitude of center point
- group · string · optionnel
  Filter by semantic group
- limit · integer · optionnel
  Max results (default 15)
- category · string · optionnel
  Filter by OSM category
- radius_miles · number · optionnel
  Search radius in miles (default 0.5)
Exemple d'appel
```
{"name": "local_intel_nearby", "arguments": {"lat": 1, "lon": 1}}
```
Exemple de retour
```
{"content": [{"type": "text", "text": "…"}]}
```
local_intel_oracle≈ 150 tokens
Pre-baked economic oracle for a ZIP. Returns: restaurant saturation (is there room for another?), price-tier gap analysis (what menu price is missing?), growth trajectory (growing/empty-nest/stable), and 3 pre-formed questions with answers baked in. No LLM needed — answers derived from population, income, business density, school count, and infrastructure signals.
Paramètres, retour & exemple (1)
Paramètres
- zip · string · requis
  ZIP code to analyze (e.g. 32081)
Exemple d'appel
```
{"name": "local_intel_oracle", "arguments": {"zip": "texte"}}
```
Exemple de retour
```
{"content": [{"type": "text", "text": "…"}]}
```
local_intel_project≈ 278 tokens
Project-type intelligence: pass a project_type (restaurant, clinic, banking, construction, real_estate, residential_development, fitness, legal, retail, auto, etc.) and get L1 ZIPs ranked by market or residential opportunity score plus L2 matching verified businesses already operating in that sector. Returns sector gap counts, HHI, population, growth state, and new-build %. Best tool for site selection and franchise expansion when you know the business type but not the ZIP.
Paramètres, retour & exemple (3)
Paramètres
- zip · string · optionnel
  Optional. Filter L2 businesses to a specific ZIP. If omitted, returns top ZIPs ranked by score.
- limit · number · optionnel
  Number of L1 ZIPs to return (default 5, max 10).
- project_type · string · requis
  Business type or project category. Examples: restaurant, clinic, banking, construction, real_estate, residential_development, fitness, legal, retail, grocery, auto, beauty, pets.
Exemple d'appel
```
{"name": "local_intel_project", "arguments": {"project_type": "texte"}}
```
Exemple de retour
```
{"content": [{"type": "text", "text": "…"}]}
```
local_intel_query≈ 304 tokens
START HERE. Natural language entry point for both market intelligence AND business routing. Ask about a market, find a business, or route a customer request. Auto-detects ZIP, industry vertical, and intent. For customer agents: "Find a restaurant in 32082 that serves lunch" or "Who can do landscaping in Ponte Vedra?" — returns the matching business so your agent can route the order to them. For market intel: "Is 32082 oversaturated with dentists?" ZIP is always required for routing — pass it explicitly or include it in the query.
Paramètres, retour & exemple (4)
Paramètres
- lat · number · optionnel
  Optional latitude (WGS84). Resolves to nearest FL ZIP. Use instead of zip for coordinate-based queries.
- lon · number · optionnel
  Optional longitude (WGS84). Required if lat is provided.
- zip · string · optionnel
  Optional ZIP override. If omitted, ZIP is detected from the query or resolved from lat/lon.
- query · string · requis
  Any plain-English market question. ZIP can be in the query or passed separately.
Exemple d'appel
```
{"name": "local_intel_query", "arguments": {"query": "texte"}}
```
Exemple de retour
```
{"content": [{"type": "text", "text": "…"}]}
```
local_intel_realtor≈ 198 tokens
Real estate intelligence for a ZIP. Ask natural-language questions: demographics, commercial gaps, flood risk, school proximity, infrastructure signals, market saturation. Returns structured data with confidence score. Trained on 100 realtor use-case prompts.
Paramètres, retour & exemple (4)
Paramètres
- lat · number · optionnel
  Latitude (WGS84) — resolves to nearest FL ZIP
- lon · number · optionnel
  Longitude (WGS84)
- zip · string · optionnel
  ZIP code to analyze
- query · string · requis
  Natural language question (e.g. "What is the flood risk for this ZIP?", "What commercial gaps exist?")
Exemple d'appel
```
{"name": "local_intel_realtor", "arguments": {"query": "texte"}}
```
Exemple de retour
```
{"content": [{"type": "text", "text": "…"}]}
```
local_intel_restaurant≈ 181 tokens
Restaurant and food service market intelligence for a ZIP. Ask about saturation scores, price-tier gaps, capture rates, corridor analysis, tidal momentum. Returns structured data with confidence score. Trained on 100 restaurant business prompts.
Paramètres, retour & exemple (4)
Paramètres
- lat · number · optionnel
  Latitude (WGS84) — resolves to nearest FL ZIP
- lon · number · optionnel
  Longitude (WGS84)
- zip · string · optionnel
  ZIP code to analyze
- query · string · requis
  Natural language question about restaurant market
Exemple d'appel
```
{"name": "local_intel_restaurant", "arguments": {"query": "texte"}}
```
Exemple de retour
```
{"content": [{"type": "text", "text": "…"}]}
```
local_intel_retail≈ 172 tokens
Retail market intelligence for a ZIP. Ask about store categories, spending capture rates, consumer profile, undersupplied niches. Returns structured data with confidence score. Trained on 100 retail business prompts.
Paramètres, retour & exemple (4)
Paramètres
- lat · number · optionnel
  Latitude (WGS84) — resolves to nearest FL ZIP
- lon · number · optionnel
  Longitude (WGS84)
- zip · string · optionnel
  ZIP code to analyze
- query · string · requis
  Natural language question about retail market
Exemple d'appel
```
{"name": "local_intel_retail", "arguments": {"query": "texte"}}
```
Exemple de retour
```
{"content": [{"type": "text", "text": "…"}]}
```
local_intel_rfq≈ 672 tokens
Route a customer request to local businesses — food orders, delivery, services, or any job. ALWAYS include the full order or ask in description (or items[]), plus business_id/business_name when ordering from a specific place. Never send a vague description like "Buy me." Use this when KDS/POS is off or for quote collection. Supports delivery (first-to-accept) and proposal (collect quotes) modes.
Paramètres, retour & exemple (16)
Paramètres
- zip · string · optionnel
  ZIP code to search businesses in
- task · string · optionnel
  Alias for description (same meaning)
- items · array · optionnel
  Structured line items, e.g. [{ "name": "chicken and broccoli", "qty": 1 }]
- dry_run · boolean · optionnel
  If true, match businesses but do NOT send email/SMS/push/rail notifications. Also auto-enabled for x-agent-id values starting with cursor-test-, test-, agent-test-, or dry-run.
- autonomy · string · optionnel · full | approve | human
  full=agent books automatically; approve=agent picks best, human confirms; human=human picks from list
- category · string · optionnel
  Business category to match, e.g. "restaurant", "food", "delivery", "landscaping", "florist", "handyman", "plumber"
- job_type · string · optionnel · delivery | proposal
  delivery = first-to-accept wins (food orders, pickups); proposal = collect quotes, pick best (services, construction)
- budget_usd · number · optionnel
  Max budget in USD (optional)
- business_id · string · optionnel
  Target a specific LocalIntel business (required when ordering from a named restaurant)
- description · string · requis
  Full human-readable request. For food: include items, e.g. "Order for McFlamingo: chicken and broccoli". Do NOT use vague text like "Buy me."
- notify_email · string · optionnel
  Email to notify for approve/human autonomy levels
- business_name · string · optionnel
  Human business name, e.g. McFlamingo — shown on the Jobs card
- customer_note · string · optionnel
  Extra note for the business (allergies, ETA, pickup vs delivery)
- pickup_address · string · optionnel
  Pickup address (delivery jobs)
- dropoff_address · string · optionnel
  Drop-off address (delivery jobs)
- deadline_minutes · number · optionnel
  Minutes until deadline (for urgent delivery jobs)
Exemple d'appel
```
{"name": "local_intel_rfq", "arguments": {"description": "texte"}}
```
Exemple de retour
```
{"content": [{"type": "text", "text": "…"}]}
```
local_intel_rfq_status≈ 82 tokens
Poll the status of an RFQ. Returns the original request, all responses received so far, and booking details if booked.
Paramètres, retour & exemple (1)
Paramètres
- rfq_id · string · requis
  UUID returned by local_intel_rfq
Exemple d'appel
```
{"name": "local_intel_rfq_status", "arguments": {"rfq_id": "texte"}}
```
Exemple de retour
```
{"content": [{"type": "text", "text": "…"}]}
```
local_intel_search≈ 171 tokens
Search businesses by name, category, or semantic group (food, retail, health, finance, civic, services).
Paramètres, retour & exemple (5)
Paramètres
- zip · string · optionnel
  Filter by ZIP code
- group · string · optionnel
  Semantic group: food | retail | health | finance | civic | services
- limit · integer · optionnel
  Max results (default 20, max 50)
- query · string · optionnel
  Text search on name/category/address
- category · string · optionnel
  Exact OSM category (restaurant, bank, dentist...)
Exemple d'appel
```
{"name": "local_intel_search", "arguments": {"zip": "texte", "group": "texte", "limit": 1, "query": "texte", "category": "texte"}}
```
Exemple de retour
```
{"content": [{"type": "text", "text": "…"}]}
```
local_intel_sector_gap≈ 234 tokens
Ranked sector gap analysis for a ZIP. Identifies NAICS sectors present at county level (CBP/CES employment) but underrepresented at ZIP (OSM business counts) — the structural whitespace in a local economy. Returns ranked opportunities with: NAICS code, sector label, county employment share, demand estimate, confidence tier, and LLM-ready signal narrative. Reads live from Postgres zip_signals — always current. Example: "NAICS 62 Health Care: Jacksonville MSA 136k healthcare employees, ZIP 32082 has no OSM healthcare listings. 28,697 residents, $121k median HHI, retiree index 1.5x. Demand: 7–10 providers." Chain into vertical agents via oracle_vertical. Cost: $0.03 pathUSD.
Paramètres, retour & exemple (1)
Paramètres
- zip · string · requis
  ZIP code to analyze (e.g. 32081, 32082, 32259)
Exemple d'appel
```
{"name": "local_intel_sector_gap", "arguments": {"zip": "texte"}}
```
Exemple de retour
```
{"content": [{"type": "text", "text": "…"}]}
```
local_intel_signal≈ 154 tokens
Investment and activity signal for a ZIP. Composite score 0-100 with band (strong_buy/accumulate/hold/reduce/avoid), top reasons, and avoid flags. Best for real estate and financial agents.
Paramètres, retour & exemple (3)
Paramètres
- zip · string · requis
  ZIP code
- agent_type · string · optionnel
  real_estate | financial | ad_placement | logistics | business_owner | civic
- query_context · object · optionnel
  Optional: { agent_id, purpose }
Exemple d'appel
```
{"name": "local_intel_signal", "arguments": {"zip": "texte"}}
```
Exemple de retour
```
{"content": [{"type": "text", "text": "…"}]}
```
local_intel_stats≈ 56 tokens
Dataset coverage stats: total businesses, confidence scores, query volume, revenue earned.
Paramètres, retour & exemple (0)
Exemple d'appel
```
{"name": "local_intel_stats", "arguments": {}}
```
Exemple de retour
```
{"content": [{"type": "text", "text": "…"}]}
```
local_intel_tide≈ 166 tokens
Tidal reading for a ZIP — temperature (0-100), direction (surging/heating/stable/cooling/receding), seasonal context. Synthesizes all 4 data layers. Best for agents deciding WHERE to act next.
Paramètres, retour & exemple (3)
Paramètres
- zip · string · requis
  ZIP code to read tidal state for
- query_context · object · optionnel
  Optional: { agent_type, agent_id, purpose }
- include_layers · array · optionnel
  Layers to include: bedrock, ocean_floor, surface_current, wave_surface (default: all)
Exemple d'appel
```
{"name": "local_intel_tide", "arguments": {"zip": "texte"}}
```
Exemple de retour
```
{"content": [{"type": "text", "text": "…"}]}
```
local_intel_zone≈ 128 tokens
Spending zone and demographic data for a ZIP code: population, income, home value, rent, ownership rate, zone score. Pass zip or lat/lon.
Paramètres, retour & exemple (3)
Paramètres
- lat · number · optionnel
  Latitude (WGS84) — resolves to nearest FL ZIP
- lon · number · optionnel
  Longitude (WGS84) — required if lat is provided
- zip · string · optionnel
  FL ZIP code
Exemple d'appel
```
{"name": "local_intel_zone", "arguments": {"lat": 1, "lon": 1, "zip": "texte"}}
```
Exemple de retour
```
{"content": [{"type": "text", "text": "…"}]}
```

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Source

https://gsb-swarm-production.up.railway.app/api/local-intel/mcp