This server gives AI assistants access to S.C.A.L.A. Score's company intelligence database of 250M+ companies across 50+ countries, enabling business research, financial analysis, and due diligence workflows.
Search Companies: Search 244M+ global companies by name, VAT number, or keyword, with filters for country (ISO 2-letter code), NACE industry code, and active/inactive status. Returns name, address, revenue, employee count, health score, and more. (1 credit)
Lookup a Company: Retrieve a full company profile by company ID or VAT number, including legal name, address, revenue, employees, health score, NACE classification, legal form, incorporation date, website, phone, and email. (1 credit)
Generate Company Reports: Create detailed health reports in three tiers:
Basic – Overview (5 credits)
Pro – Financial analysis (10 credits)
Enterprise – Full due diligence (20 credits)
Database Statistics: View total company count, countries covered, and last update date. (free)
List Countries: See all countries in the database along with company counts per country. (free)
Check Credits: View remaining API credits, current subscription plan, and credit reset date. (free)
An MCP server that turns Claude into a full business operating system. Manage your CRM, send invoices, book appointments, chat with your AI assistant, run workflows, and search 250M+ companies — all without leaving your AI conversation.
npx -y scala-mcp-serverOne command. Set your API key and go:
SCALA_API_KEY=your-key npx -y scala-mcp-serverGet a free API key at app.get-scala.com — 14-day trial, no credit card.
Related MCP server: sk-registers-mcp
"Show my sales pipeline" "Create a contact for Maria Rossi at Ferrero" "Move the Johnson deal to 'proposal' stage" "Show the timeline for contact abc-123"
"What slots are available tomorrow at 2pm?" "Book a consultation for Marco next Thursday at 10am" "Cancel booking #456"
"List all overdue invoices" "Create an invoice for the Q3 consulting work — EUR 4,500" "Send invoice #789 to the client"
"Ask SARA what happened with customer complaints this week" "Show me SARA's business insights" "What alerts does SARA have for me?"
"What's my business health score?" "Show cash flow for the last 6 months" "Give me a financial summary"
"Show restaurant KPIs — covers, avg ticket, food cost" "List all vehicles in the dealership inventory" "What are this month's real estate commissions?" "Show studio project milestones"
"Find the top 10 SaaS companies in Germany" "Look up Ferrero's financial health" "Compare construction companies in Milan vs Munich" "Generate a due diligence report on company XYZ"
"List all active workflows" "Run the weekly report workflow" "Show workflow success rates"
npx @smithery/cli mcp add Alessandro114/scala-mcp-server --config '{"scalaApiKey":"your-key"}'Add to your claude_desktop_config.json:
{
"mcpServers": {
"scala": {
"command": "npx",
"args": ["-y", "scala-mcp-server"],
"env": {
"SCALA_API_KEY": "your-api-key"
}
}
}
}{
"mcpServers": {
"scala": {
"command": "npx",
"args": ["-y", "scala-mcp-server"],
"env": {
"SCALA_API_KEY": "your-api-key"
}
}
}
}claude mcp add scala -e SCALA_API_KEY=your-key -- npx -y scala-mcp-serverSCALA_API_KEY=your-key npx -y scala-mcp-serverTool | Description | Credits |
| Search 250M+ companies by name, VAT, keyword | 1 |
| Full company profile by ID or VAT | 1 |
| Health report (basic/pro/enterprise) | 5-20 |
| Database statistics | 0 |
| Countries with company counts | 0 |
| API credits and plan info | 0 |
Tool | Description |
| List/search contacts with pipeline stage filter |
| Create contact with name, email, company, tags |
| Update any contact field |
| Pipeline view grouped by stage |
| Full activity timeline for a contact |
Tool | Description |
| Available time slots for a business |
| Create booking with auto-confirmation email |
| Cancel a booking |
Tool | Description |
| List invoices with status filter |
| Create invoice (multi-provider) |
| Email invoice to customer |
| Get invoice PDF |
Tool | Description |
| Chat with SARA about your business |
| List conversation history |
| AI-generated business insights |
| Active business alerts |
| Proactive AI suggestions |
Tool | Description |
| Revenue, expenses, profit overview |
| Business health score (0-100) |
| Cash flow by period |
Tool | Description |
| KPIs for any vertical (DineOS, PropertyOS, etc.) |
| List records from any vertical table |
| Create records in any vertical |
| Check active modules |
Tool | Description |
| List automation workflows |
| Execute a workflow |
| Workflow statistics |
The server exposes static resources that Claude can read for context:
Resource | URI | Description |
Pricing |
| Current plans, enterprise tiers, add-ons |
Verticals |
| All 20 industry modules with features |
Capabilities |
| Full platform feature list |
Pre-built prompt templates for common workflows:
Prompt | Description |
| Generate a tailored enterprise pitch |
| Comprehensive business intelligence report |
| Personalized onboarding checklist |
Module | Industry |
DineOS | Restaurants & F&B |
PropertyOS | Real Estate |
AgencyOS | Marketing Agencies |
MotorOS | Car Dealerships |
TravelOS | Travel Agencies |
StudioOS | Architecture & Engineering |
BeautyOS | Beauty & Wellness |
CleanOS | Cleaning & Facility Management |
ShopOS | Retail |
WellnessOS | Fitness & Wellness |
DermalyOS | Dermatology & Medical |
ServiceOS | Field Services |
ProjectOS | Project Management |
NetworkOS | MLM & Referral |
PraxisOS | Medical Practices |
TrichoOS | Hair & Trichology |
ReputationOS | Reputation Management |
AdOS | Advertising |
LandIQ | Real Estate Development |
Your AI <--> MCP Protocol <--> scala-mcp-server <--> S.C.A.L.A. API
|
33 tools + 3 resources + 3 prompts
|
CRM - Invoicing - Bookings - SARA AI - Finance
Workflows - 20 Verticals - 250M+ Companiesenrich-companies (npm) — CLI to enrich CSV files with company data
enrich-companies (PyPI) — Same tool, Python version
scala-score (PyPI) — Python SDK
world-company-database — Curated list of 40+ free company databases
Score API Docs — REST API documentation
n8n Integration — n8n workflow nodes
The server includes 5 pre-built skills for Claude Code (in skills/):
Skill | What it does |
| Morning briefing — alerts, invoices, pipeline, KPIs, AI suggestions |
| Health score + cash flow + recommendations |
| Competitor research from 250M+ companies |
| Pre-meeting company deep dive + talking points |
| Overdue invoices grouped 30/60/90+ days + send reminders |
git clone https://github.com/Alessandro114/scala-mcp-server.git
cd scala-mcp-server
npm install
npm run dev # Run with tsx (hot reload)
npm run build # Compile TypeScriptMIT — Copyright (c) 2026 Alessandro Binda / S.C.A.L.A. AI OS
Check your remaining API credits, current plan, and reset date.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Describes read-only behavior but lacks details on authentication, rate limits, or any side effects. With no annotations, description carries full burden.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, 10 words, front-loaded with action and resource. No wasted text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Explains return items (credits, plan, reset date) despite lacking output schema. Could add more detail but sufficient for a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters, so description adds meaning by specifying what is checked (credits, plan, reset date). Baseline 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the action (check) and the resource (credits, plan, reset date). Distinct from sibling tools like company_report or database_stats.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implicitly indicates use when needing credit information. No explicit when-not or alternatives, but siblings are clearly different functions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Generate a detailed company health report. Available types: basic (overview, 5 credits), pro (financial analysis, 10 credits), enterprise (full due diligence, 20 credits).
| Name | Required | Description | Default |
|---|---|---|---|
| company_id | Yes | Company ID to generate report for | |
| type | No | Report type (default: basic) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden for behavioral disclosure. It reveals that different report types consume credits (5, 10, 20), which is useful. However, it does not mention permissions, whether the report is cached, or any side effects beyond credit usage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences that are front-loaded with the action and then detail the options. Every word earns its place with no redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description should compensate by describing the report structure. It lists types but does not explain what data each type returns. For a report generation tool, this is a meaningful gap, but the credit cost info partially compensates.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds value by specifying credit costs for each enum value of the `type` parameter, which is not present in the schema. This helps the agent understand the trade-offs between report types.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Generate a detailed company health report', which is a specific verb+resource. It distinguishes from siblings like `lookup_company` and `search_companies` by focusing on report generation, but does not explicitly contrast with them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides context on when to use each report type based on credit costs and depth (basic, pro, enterprise), but does not offer guidance on when to choose this tool over alternatives like `lookup_company` or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get S.C.A.L.A. Score database statistics: total companies, countries covered, last update date.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description only mentions output fields but does not disclose read-only nature, authorization needs, rate limits, or other behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no fluff, front-loaded with the action 'Get' and lists key statistics efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for a parameterless tool with no output schema. Describes what the user gets, though could mention data source or refresh frequency for completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Zero parameters, so schema coverage is 100% by default. Description adds value by specifying output fields (total companies, countries, last update), beyond the empty schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves database statistics (total companies, countries covered, last update date), distinguishing it from sibling tools like lookup_company or search_companies.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when or when not to use. Usage is implied as a general overview tool, but alternatives like check_credits or list_countries are not mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List all countries available in the database with company counts per country.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description indicates a read-only operation but doesn't disclose any behavioral traits like performance, ordering, or pagination. Adequate for a simple list tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with no waste, front-loaded with verb. Efficient and clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Description hints at output (company counts) but lacks details on format, ordering, or examples. With no output schema, more output description would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has zero parameters, so description doesn't need to add parameter info. Baseline score of 4 applies due to high schema coverage and no parameter details needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool lists all countries with company counts, using specific verb and resource. It distinguishes from sibling tools like lookup_company which target individual companies.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when or when-not guidance provided. Context implies it's for getting an overview, but no comparison to alternatives like database_stats.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get detailed company information by ID or VAT number. Returns full company profile: legal name, address, revenue, employees, health score, NACE classification, legal form, incorporation date, website, phone, email.
| Name | Required | Description | Default |
|---|---|---|---|
| company_id | Yes | Company ID or VAT number (e.g. IT02727330014) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full burden. It discloses that the tool reads and returns a detailed profile, but does not mention error handling or authentication requirements. However, for a simple lookup, it is sufficiently transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the purpose and lists return fields without fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no output schema, no annotations), the description provides enough context on what the tool returns. It could mention error behavior, but overall it is complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds no extra meaning beyond the schema's description of the parameter as 'Company ID or VAT number'. It is consistent but not more helpful.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'detailed company information' by ID or VAT number. It lists the returned fields, distinguishing it from siblings like search_companies or check_credits.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when a specific company ID or VAT number is available, but it does not explicitly state when to use this tool versus alternatives like search_companies or company_report.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search 244M+ companies worldwide by name, VAT number, or keyword. Filter by country (ISO 2-letter code), NACE industry code, and active/inactive status. Returns company name, address, revenue, employees, health score, and more.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Company name, VAT number, or keyword to search | |
| country | No | ISO 2-letter country code (e.g. IT, DE, FR, US, GB) | |
| nace | No | NACE industry code (e.g. 56.10 for restaurants, 62.01 for software) | |
| status | No | Filter by company status | |
| limit | No | Max results (1-100, default 10) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must disclose behavior. It mentions it is a search operation returning data but does not discuss rate limits, pagination, or idempotency. Lack of behavioral details beyond basic read nature lowers score.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, efficient, front-loaded with purpose. No redundant or verbose text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a search tool with no output schema, description covers basic functionality but omits pagination behavior, result format, and details on 'and more' fields. Incomplete for full agent decision-making.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so description adds little beyond what schema provides. It lists parameter categories but no additional constraints or examples. Baseline at 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses strong action verb 'Search' and specifies resource 'companies', adding scope '244M+ worldwide'. It lists searchable criteria and return fields, clearly distinguishing from sibling tools like lookup_company (which likely retrieves by ID).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Description does not provide explicit guidance on when to use this tool over siblings like lookup_company or company_report. Usage context is implied from the word 'Search' but no when-not-to or alternative recommendations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
v0.1.0check_creditscompany_reportdatabase_statslist_countrieslookup_companysearch_companiesEach tool has a clearly distinct purpose: credits check, report generation, database stats, country listing, company lookup, and company search. There is no overlap or ambiguity.
Most tools follow a verb_noun pattern (list_countries, lookup_company, search_companies, check_credits), but company_report and database_stats are noun_noun, creating inconsistency.
With 6 tools, the set is well-scoped for a company database service. Each tool covers an essential operation without being overly numerous or sparse.
The tool set covers all core interactions: search, detailed lookup, country filtering, database statistics, report generation, and account management. No obvious gaps for a read-oriented data provider.
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
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