"Do Not Train" for Sensitive Public MCP Servers

[MarlzRana]

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• I have verified that this discussion would not be more appropriate as an issue in a specific repository
• I have searched existing discussions to avoid duplicates

Discussion Topic

Hey everyone! 😄

I am from the #financial-services-wg, and as you know, we deal with sensitive data and are heavily regulated. We want to be able to give our users the ability to query about their banking information in their favorite AI assistants (ChatGPT, Claude, Gemini), via an MCP server proposition. However, a friction point is that, typically by default, most AI assistant providers train on consumer messages, which, if possible, we would like to avoid.

In an ideal world, where all parties are cooperative, I think something like this would mostly work:

• First, let's define a sensitive MCP server as one that does not wish to have chats that have made use of it, be used for future training
• In the InitializeRequest, we add an attribute, where the MCP client can express that they support the ability to not train on chats if a sensitive MCP server requests
• Sensitive MCP servers could reject the initialization request if the MCP client has no support to not train on chats that utilize it
• In the _meta property of InitializationResult, reserve a key such as io.modelcontextprocol/do-not-train that sensitive MCP servers would set
• Model providers that support the ability to not train on particular chats would respect the io.modelcontextprocol/do-not-train mark (if at least one tool call were made to a sensitive MCP server during a chat, it would exclude the rest of that particular chat from training)
• The above-described approach relies on trust and could be easily exploited by bad actors, so as an additional step, we could IP allowlist our sensitive MCP server to only respond to trusted model providers

Playing devil's advocate to the approach I described above:

• Can we rely on model providers wanting to support this? Is it in their best interests? Can we get MCP servers that provide sensitive data without this?
• In chats configured with multiple MCP servers, this still doesn't prevent sensitive data from being fed out of a sensitive MCP server to another MCP server that the sensitive MCP server does not trust. (Maybe an additional mechanism to tell MCP clients to ensure that we are the only MCP server in a chat?)

Curious to hear:

• The community's feelings on this
• If any other organizations are in a similar dilemma
• If anyone already has a solution
• Any other proposed solutions

[MarlzRana]

Closing in favour of: modelcontextprotocol/modelcontextprotocol#2185

[kina279]

If it is sensitive because data can be leaked,. it's not worth the effort not to train for the sake of saving data ,.just flood with a continuous stream of data in case of unauthorized access, preset page,. sub, 31. jan 2026. 21:40 Marlin Ranasinghe ***@***.***> je napisao/la:

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Pre-submission Checklist - I have verified that this discussion would not be more appropriate as an issue in a specific repository - I have searched existing discussions to avoid duplicates Discussion Topic Hey everyone! 😄 I am from the #financial-services-wg, and as you know, we deal with sensitive data and are heavily regulated. We want to be able to give our users the ability to query about their banking information in their favorite AI assistants (ChatGPT, Claude, Gemini), via an MCP server proposition. However, one of the friction points is that, typically by default, most AI assistant providers train on consumer messages, which, if possible, we would like to avoid. In an ideal world, where all parties are cooperative, I think something like this would mostly work: - First, let's define a sensitive MCP server as one that does not wish to have chats that have made use of it, be used for future training - In the InitializeRequest, we add an attribute, where the MCP client can express that they support the ability to not train on chats if a sensitive MCP server requests - Sensitive MCP servers could reject the initialization request if the MCP client has no support to not train on chats that utilize it - In the _meta property of InitializationResult, reserve a key such as io.modelcontextprocol/do-not-train that sensitive MCP servers would set - Model providers that support the ability to not train on chats would respect the io.modelcontextprocol/do-not-train mark (if at least one tool call was made to a sensitive MCP server during a chat, it would exclude the rest of that particular chat from training) - The above described approach relies on trust, and could be easily exploited by bad actors, so as an additional step, we could whitelist our sensitive MCP server to only respond to trusted model providers Playing devil's advocate to the approach I described above: - Can we rely on model providers wanting to support this? Is it in their best interests? Can we ever get MCP servers that provide sensitive data without this? - In chats configured with multiple MCP servers, this still doesn't prevent sensitive data from being fed out of a sensitive MCP server to another MCP server that the sensitive MCP server does not trust. (Maybe an additional mechanism to tell MCP clients to ensure that we are the only MCP server in a chat?) We can mostly "deal" with these issues by running users through a strong consent flow, but I can imagine there are others who cannot. Curious to hear the community's feelings, if anyone already has a solution, or any other proposed solutions! 🤝 — Reply to this email directly, view it on GitHub <#673>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/BUS22LQS67QAZ4KW3MXISEL4JUHMVAVCNFSM6AAAAACTRRHK6SVHI2DSMVQWIX3LMV43ERDJONRXK43TNFXW4OZZGQYTEOBVG4> . You are receiving this because you are subscribed to this thread.Message ID: ***@***.***>