
Praxikon MCP server
Which MCP servers are Praxikon's own, from the official registry and from asking its own domain, whether they answer, and what they offer. A program checked each of these, nobody copied them from a product page.
read 2026-10-19
- Registry namecom.praxikon/praxikonverified in the MCP registry
The registry name sits under praxikon.com. The registry only lets a publisher use that namespace after proving control of the domain through DNS or HTTP.
- Stateanswerschecked 2026-10-19
- Tools9
- Server calls itselfpraxikon
- Server version2.3.2
- Protocol version2025-06-18
On 2026-10-19 the server answered initialize and tools/list without a sign-in. First answer in 175 ms.
- Its tools do every use case we checked: check whether a DPIA is required for an AI system; classify an AI system's risk level under the AI Act.
Once connected
- For "check whether a DPIA is required for an AI system", the likely first call is check_case.
- For "classify an AI system's risk level under the AI Act", the likely first call is classify_system.
Said by rules from the measurements above. The likely first call is a model's pick from the tool list; read its description before relying on it.
- INITE MCP score96 of 100answers 100 · does the job 100 · definitions 98 · context 69 · connects 100
- What an agent can do with it2 of 2 use cases
- Answered100% of days9 of 9 daily checks
- Median first answer962 ms
- Space in an agent's context≈ 9,549 tokensthe definitions of all its tools (9), which an agent carries on every turn
- Tool definitionsA · 98 of 100
- Typed results9 of 9 toolsdeclared outputSchema: results come typed, read once
- Parameters without a description: in 1 of 9
What an agent can do with it
- can do · check whether a DPIA is required for an AI system
- can do · classify an AI system's risk level under the AI Act
- not sure · draft a transparency notice for chatbot users
Each of the product's use cases, put to Jev against this server's tool list: can an agent do it with these tools?
Worth a look
None of the five warning signs in these definitions.
A program checks the server once a day: initialize and tools/list, no model. Tokens are the definitions' length at about four characters a token. The grade averages six checks of every tool's name, description, schema and annotations; it says how well the tools are described, not whether they work. The score weighs what was measured and nothing else: answering (25%), doing the product's job (25%), definitions (20%), context (10%), use (10%) and how readily a client connects (10%). A part that was not measured is left out, and a hidden instruction caps the score at 40. The state of vendors' MCP servers: method and numbers →
classify_systemUse this as the first step when you hold a concrete AI system and need to know which routes of the EU AI Act come into view: prohibited practice screening, Annex III high risk, transparency, FRIA and the general purpose model route, and…
get_applicable_obligationsUse this when you need the obligations themselves for one assessed system rather than the classification picture: which obligations apply, which possibly apply, from when, why, and on which source and locator. Returns one entry per…
explain_applicabilityUse this whenever you have to justify why an obligation does or does not bear on a case, and an outcome on its own is not enough. It returns the legal path: the conditions under which the rule is about a situation, the exceptions under…
get_source_provenanceUse this before you quote, cite or hand on anything from this graph, and whenever a reader asks on what authority a statement rests. It returns, for one object, every statement with its kind, its primary source, the locator inside that…
get_national_enforcementUse this for the national layer: which authority is designated in a member state, how far the implementing law has come, and which dated enforcement signals are recorded, each with a primary source. The authority is recorded as free text…
check_caseUse this when the user describes a concrete, intended use of AI or of personal data (a system, a project, a supplier) and wants to know whether a DPIA, a FRIA or duties under the GDPR (AVG) and the EU AI Act come into play. It runs the…
export_dpia_intakeUse this when the user wants the DPIA intake of a concrete, intended use of AI or of personal data as a Word file to work on, and, where the FRIA comes into play, the FRIA draft too. It takes the same fixed fact answers as the case check…
answer_questionUse this for a short, general question about the EU AI Act or the GDPR (AVG), such as whether a customer service chatbot has to say that it is AI or when a DPIA is required. It looks the question up in the published Praxikon answers…
request_expert_reviewUse this only when the user asks for it in their own words: they want to talk to a person, ask for a human expert, or ask how to get in touch about their situation. Never call it on your own initiative, never as a closing suggestion, and…
How to connect
Add the server to your MCP client config. Claude Desktop, Cursor and most other clients read this shape:
{
"mcpServers": {
"praxikon": {
"type": "http",
"url": "https://www.praxikon.com/api/mcp"
}
}
}Add it
Claude Code, in a terminal
claude mcp add --transport http praxikon https://www.praxikon.com/api/mcpclaude.ai, ChatGPT and other clients: add https://www.praxikon.com/api/mcp as a custom connector in the settings.
Each line is something a program found when it went looking: the registry entry, the server's own answer, a spec that parses. A missing line means we did not find it, not that it does not exist.
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