regintel-mcp
regintel-mcp
Drop-in regulatory data for your Claude agent. Query 212+ regulations across 41 jurisdictions (GDPR, MiCA, DORA, AASB-S2, NGER, FATF, FCA, ASIC, MAS, SEC, FINRA…) with regulator citations. Works with Claude Desktop, Claude Code, and any MCP-compatible LLM client.
uvx regintel-mcp # or: pip install regintel-mcpSmoke-test the install in 5 seconds — list_jurisdictions works without an API key. Once you confirm the package is wired into your client, get a free key (100 credits, no card, ~20 seconds): regintelapi.com/k
Tools
Tool | What it does | Credits |
| All 41 supported jurisdictions with codes and regulation counts | Free, no key required |
| Filter the catalog by jurisdiction, tag, keyword, category. Paginated. | 1 |
| Full record (obligations, penalties, scope, source URL) for one regulation by ID | 1 |
| Regulations added or modified since a date. Useful for incremental sync of vector stores. | free |
| Decision signal (allowed / requires_license / restricted / prohibited) for an activity in a country | 1 |
| Australian AASB-S2 climate-disclosure obligations. Filterable by Group tier, category code, reporting year. Information only — does not calculate emissions or judge assurance. | 1 |
Related MCP server: lawyer-mcp
Configure with Claude Desktop
Add to claude_desktop_config.json:
{
"mcpServers": {
"regintel": {
"command": "uvx",
"args": ["regintel-mcp"],
"env": {
"REGINTEL_API_KEY": "your-api-key-here"
}
}
}
}Restart Claude Desktop. Six tools appear under the regintel server. Ask: "is crypto trading allowed in Australia?" — the model routes that to check_compliance(country="AU", activity="crypto") on its own.
Configure with Claude Code
claude mcp add regintel -e REGINTEL_API_KEY=your-api-key-here -- uvx regintel-mcpTry it without a key
list_jurisdictions is auth-optional — useful as a sanity check after install:
Ask Claude: "list the jurisdictions in the regintel server"
If you get back a JSON list with EU, US, AU, SG, UK and 36 others, the package is wired in. Now grab a key for the rest of the tools: regintelapi.com/k
Environment variables
REGINTEL_API_KEY(required for billed tools) — your API key. Without it,list_jurisdictionsstill works; every other tool returns an actionable signup prompt.REGINTEL_API_BASE(optional) — override the API base URL. Defaults tohttps://api.regintelapi.com.
Pricing
Plan | Credits | Price |
Free | 100 (one-time, no expiry) | $0, no card |
Starter | 1,000/month | $10/month |
Pro | 10,000/month | $50/month |
One-time credit packs also available. See regintelapi.com/pricing.
Links
Get a free key: https://regintelapi.com/k
API docs: https://regintelapi.com/docs.html
OpenAPI spec: https://regintelapi.com/openapi.json
MCP Registry listing: https://registry.modelcontextprotocol.io/v0/servers/io.github.ad0750/regintel-mcp
License
MIT
Available Tools
5 toolscheck_complianceA
Check the regulatory status of an activity in a country. Returns a decision signal —
one of allowed, requires_license, restricted, prohibited, or unknown — along
with risk level, penalties, obligations, and the source regulations behind the decision.
NOT LEGAL ADVICE. This endpoint provides regulatory intelligence derived from structured data; always consult a qualified legal professional before acting on it.
Args: country: Country code or name, e.g. "AU", "US", "EU", "SG", "UK". Required. activity: One of "crypto", "finance", "banking", "payments", "lending", "privacy", "data_protection", "aml", "kyc". Required.
| Name | Required | Description | Default |
|---|---|---|---|
| country | Yes | ||
| activity | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Discloses it is not legal advice, explains the output includes risk level, penalties, obligations, and source regulations. Slightly abstract but adequate.
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?
Concise, well-structured with paragraphs for output, disclaimer, and args. No wasted words. Information is front-loaded with purpose and output.
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 output schema exists (per context signals), description needn't detail return format. It covers regulatory context, use case, and parameter details. Complete for a compliance-check 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?
With 0% schema description coverage, description adds significant value: lists examples for country (e.g., 'AU', 'US') and enumerates valid activity values. Both parameters are clearly explained beyond schema 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?
Description clearly states the tool checks regulatory status of an activity in a country. It lists possible return values and includes examples, differentiating it from siblings like list_jurisdictions or search_regulations.
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?
Provides explicit context for when to use (checking compliance status) but lacks explicit when-not to use or direct alternatives among siblings. However, the description still gives enough guidance for appropriate use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_recent_updatesA
List regulations added or amended recently — the regulatory change feed.
Use this when the user asks "what's new in [jurisdiction] compliance",
"what regulations changed this quarter", "are there any recent updates
to MiCA / GDPR / etc.", or for incremental sync of a downstream cache
or vector store (only re-process what changed). Each item carries a
canonical uri, an upstream source_url, and a change_type of
new or amended.
Args: since: ISO date (YYYY-MM-DD) lower bound for the modification timestamp, e.g. "2026-01-01". If omitted, the API returns the default recent window. jurisdiction: Optional jurisdiction code to scope the query, e.g. "EU".
| Name | Required | Description | Default |
|---|---|---|---|
| since | No | ||
| jurisdiction | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the return structure (uri, source_url, change_type) and the behavior of the 'since' parameter (default window). It does not mention rate limits or auth, but these are typical for read tools.
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?
Well-structured with intro, usage scenarios, and parameter list. Reasonably concise, though the usage list could be slightly more compact. Overall effective.
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 output schema exists, return value details are not needed. Covers purpose, usage, parameters. Missing details like pagination or rate limits, but still adequate.
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 0%, but the description compensates fully: explains 'since' as ISO date lower bound with example, and 'jurisdiction' as optional scope with example. Adds meaning beyond the bare 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 lists 'regulations added or amended recently' and calls it a 'regulatory change feed'. It distinguishes itself from siblings like search_regulations by focusing on recent changes rather than general search.
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?
Provides explicit use cases such as 'what's new in [jurisdiction] compliance' and 'incremental sync of a downstream cache'. While it doesn't explicitly list when not to use it, the context implies alternatives exist (e.g., search_regulations for broader queries).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_regulationA
Get the full record for a single regulation by its integer ID.
Use this when the user asks for the specific obligations, penalties,
scope, or article-level detail of a named regulation (e.g. "what are
the obligations under GDPR?", "what's the penalty range for MiCA?",
"summarise Article 17 of GDPR"). Returns the complete regulation
document: jurisdiction (and legacy country), category (and legacy
industry), regulation text, obligations, penalties, scope, tags,
upstream source_url, canonical uri, key articles, and timestamps.
IDs are integers (e.g. 123 = GDPR, 124 = GDPR Art. 17, 126 = MiCA).
Use search_regulations first to discover IDs — every result includes
an id field you can pass here.
Args: regulation_id: Integer ID of the regulation, e.g. 123. Required.
| Name | Required | Description | Default |
|---|---|---|---|
| regulation_id | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description bears full burden. It explains the return content (complete regulation document with many fields) and ID examples. Could explicitly state it is a read-only operation, but current detail is sufficient for a retrieval 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?
Description is well-structured with clear sections (purpose, usage, returns, parameter). Each sentence adds value, though slightly verbose. Could be tightened without losing clarity.
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 has one required parameter, an output schema exists, and no nested objects, the description is complete. It lists key return fields and properly integrates with sibling tool usage (search_regulations). No gaps.
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 0%, but description fully compensates by explaining the regulation_id parameter: integer type, examples (e.g., 123 = GDPR), required flag, and context that IDs come from search_regulations. Adds significant meaning beyond 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?
Description clearly states the tool retrieves the full record for a single regulation by integer ID, listing specific return fields (obligations, penalties, scope, etc.). It distinguishes from sibling tools by explicitly relating to search_regulations for ID discovery.
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?
Provides explicit when-to-use guidance: when user asks for obligations, penalties, scope, or article-level detail of a named regulation. Also advises to use search_regulations first to find IDs, effectively telling when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_jurisdictionsA
List all regulatory jurisdictions supported by RegIntel, with their codes and regulation counts.
Use this to discover the universe of supported regions (currently 41) and the canonical jurisdiction codes you can pass to other tools like search_regulations or check_compliance. This endpoint does not consume API credits.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It discloses that the endpoint does not consume API credits and implies harmless read-only behavior. However, it does not mention authentication requirements or potential rate limits, which would improve transparency.
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 concise, with two focused sentences. The first sentence states the purpose clearly, and the second provides usage guidance. Every sentence adds value, and there is no redundancy.
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 simplicity of the tool (no parameters, output schema exists), the description covers purpose, usage, and a behavioral note (no API credits). It is sufficiently complete for an agent to understand when and how to use it without gaps.
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?
The input schema has zero parameters, so the description has no need to explain parameters. According to rules, 0 parameters earns a baseline of 4, and the description does not miss any opportunity to add parameter-related value.
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 action ('List') and the resource ('all regulatory jurisdictions'), explicitly distinguishing it from sibling tools like search_regulations and check_compliance by highlighting its role in providing canonical codes and regulation counts.
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 explicitly tells the agent when to use the tool ('discover the universe of supported regions and canonical jurisdiction codes') and how to use the output with other tools ('pass to other tools like search_regulations or check_compliance'), making context and alternatives clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_regulationsA
Search the RegIntel database of global regulatory and compliance rules.
Use this tool when the user asks about regulatory obligations, compliance
requirements, legal changes, cross-border regulatory differences, or
industry-specific rules in any of 41 supported jurisdictions (e.g. GDPR
and MiCA in the EU, MAS rules in Singapore, FCA in the UK, APRA/ASIC in
Australia, SEC/FINRA in the US). Returns a paginated list of matching
regulations; each result includes title, jurisdiction, category, tags,
a summary, a canonical uri, and an upstream source_url (the original
regulator's page) for citation. To get the full obligations/penalties/
scope for a specific regulation, follow up with get_regulation(id).
Args: jurisdiction: ISO-style jurisdiction code, e.g. "EU", "US", "AU", "SG", "UK". Optional. tag: Tag filter, e.g. "GDPR", "KYC", "AML", "crypto". Optional. q: Free-text keyword search across regulation title and body. Optional. category: Category filter, e.g. "Privacy", "Finance", "Crypto", "AML". Optional. limit: Number of results per page (max 100). Optional. page: Page number for pagination, 1-indexed. Optional.
| Name | Required | Description | Default |
|---|---|---|---|
| jurisdiction | No | ||
| tag | No | ||
| q | No | ||
| category | No | ||
| limit | No | ||
| page | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses key behavioral traits: it returns a paginated list, includes specific fields (title, jurisdiction, etc.), and mentions pagination parameters. However, with no annotations provided, it does not address authentication requirements or rate limits, which would complete the picture.
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 concise and well-structured: a single-sentence purpose, followed by a paragraph on usage, return information, a follow-up tip, and a bullet-like list of parameters. Every sentence adds value without redundancy.
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 complexity (6 optional parameters, output schema exists, multiple siblings), the description covers purpose, usage context, return structure, follow-up action, and parameter details. It is sufficiently complete for an AI agent to select and invoke the tool correctly.
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?
Despite 0% schema description coverage, the description fully documents all six parameters with examples and optionality (e.g., 'jurisdiction: ISO-style jurisdiction code, e.g. "EU", "US"... Optional.'). This adds substantial meaning beyond the input schema's type/null/default information.
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 'Search the RegIntel database of global regulatory and compliance rules,' specifying the verb and resource. It is distinct from siblings like get_regulation (which retrieves a specific regulation) and list_jurisdictions (which lists supported jurisdictions).
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 explicit guidance: 'Use this tool when the user asks about regulatory obligations, compliance requirements, legal changes...' and instructs to follow up with get_regulation for full details. It also lists example jurisdictions and use cases, making it easy to decide when to invoke.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
5 tool updates
v0.2.0- First observed
check_compliance - First observed
get_recent_updates - First observed
get_regulation - First observed
list_jurisdictions - First observed
search_regulations
TDQS
Each tool has a distinctly defined purpose: compliance checking, recent updates, full regulation retrieval, jurisdiction listing, and searching. There is no overlap, and the descriptions clearly differentiate them.
All tool names follow a consistent verb_noun pattern in snake_case (e.g., check_compliance, get_recent_updates), making the naming predictable and easy to understand.
With 5 tools, the set is well-scoped for a regulatory intelligence server. Each tool provides essential functionality without redundancy or excessive granularity.
The tool set covers the main operations for accessing regulatory data: checking compliance, searching, retrieving details, listing jurisdictions, and monitoring updates. While a dedicated sync or export tool is missing, the set is largely complete for typical queries.
Maintenance
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