MIND
How MIND Uses the Claude Compliance API to Make DLP Smarter (2026-09-29) commercialThe section your link pointed to isn't on MIND's page any more, so we've brought you to the top.
MIND data security platform puts data loss prevention (DLPDLPData Loss Prevention: a category of controls that inspect and block sensitive data from leaving an organisation via email, web, or removable media, giving cyber tools a policy enforcement layer over data in motion and at rest.) and insider risk management (IRMIRMInsider Risk Management: a discipline focused on detecting and responding to threats from employees or contractors with legitimate access, giving cyber tools behavioral analytics and policy-enforcement hooks for internal actors.) on autopilot - automatically identify, detect & prevent data leaks
claude mcp add --transport http mind-mcp https://mcp.mind.io -s user claude mcp login mind-mcp
Summary
MIND is a commercial data-security platform that automatically identifies, detects, and prevents data leaks by managing data loss prevention and insider risk. It is run as a service via a Model Context ProtocolModel Context ProtocolModel Context Protocol, a standard for connecting AI applications to external tools and data sources. A compatible server exposes capabilities an assistant can use through a common interface. (MCPMCPModel Context Protocol, a standard for connecting AI applications to external tools and data sources. A compatible server exposes capabilities an assistant can use through a common interface.) server, and it is for security teams interested in data-security-posture. Its documentation positions it alongside other MCP-capable AI clients. The platform was launched in 2023 and has had 29 releases in the tracked window.
MIND data security platform puts data loss prevention (DLP) and insider risk management (IRM) on autopilot - automatically identify, detect & prevent data leaks
How MIND helps
Which open issues in my environment count as real data-leak risk right now?
queries the live issue inventory in plain language and returns the open items with their current status, without writing query syntax against the console
Which of my DLP policies actually match how data is being used, versus what someone wrote months ago?
the Policy Producer Agent watches observed environment activity and continuously refines policy definitions against it, flagging where behavior has drifted from the rule
Who is asking for exceptions to policy, and are their justifications legitimate?
the Reason Reviewer Agent checks each override justification against organizational guidance at the moment it's submitted, rather than leaving it for a later audit
When a leak is confirmed, does remediation happen before more data walks out the door?
the Rapid Response Agent carries out approved remediation actions immediately and only stops to escalate when a step requires human sign-off
Who has access to what, and does it match who should?
answers natural-language queries against the resource inventory and the current users-and-roles list, so mismatches surface without a separate export
Can I show what happened to a resource over time for an audit?
pulls from the audit log in response to a plain-language question, returning the history tied to that resource or user
Languages
Score card
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Shipping velocity releases a month, last 12 months
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Documentation quality release-notes rubric, 0–100
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Breaking-change discipline how rarely a release breaks users, and notice given
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Maintenance risk quiet time against its own cadence, maintainers
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Innovation & surface new capabilities, API and MCP surface
Five scores for MIND, each built from the releases, notes and API history this site tracks — and, on Researcher and Business, where it stands among every measured tool in its category and how that has moved.
Score cards are part of every paid plan.
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Blank means never measured; nothing here is a filled-in zero.
Peer standings are included with Researcher and Business. See how this tool ranks against its competitors, using data we don't publish anywhere else.
See plans →Each score is 0–100 on a published rubric, derived from data this site already shows. A dimension we cannot measure says so — it is never scored 0 and never enters a rank.
How this is scored
- Shipping velocity — releases a month over the last 12 months, on a log scale where 16 a month scores 100. Needs 3 releases in the window.
- Documentation quality — the release-notes rubric published on the analytics page, unchanged.
- Breaking-change discipline — the share of releases carrying a breaking change (none scores 100, half or more scores 0). Only projects that label breaking changes are measured: a clean record cannot be told from an unlabelled one.
- Maintenance risk — quiet time measured against the tool's own release cadence (quiet longer than 90 days and three typical gaps scores 0), plus the number of active maintainers and whether contributors are growing, where known. Higher is lower risk.
- Innovation & surface — new capabilities in the feature ledger this year, API and MCP operations added, and the share of commits that are features: the mean of whichever we hold.
- Community health (open-source tools only) — each is a direction, not a size: contributors this year against last, the bus factor now against a year ago, and issues closed per issue opened, where steady scores 50, doubled 100 and halved 0; plus the median time to a maintainer's first reply (an hour scores about 100, a month or more 0). A commercial card has no repository and carries none of the four.
- Documented delivery (commercial tools) — when a vendor's documented new capabilities have slowed against its own baseline, that counts against the overall standing as heavily as two low dimensions. Steady delivery, or too little history to judge, leaves the standing alone; it is never a sixth score.
- Open-source tools are scored on repository signals; commercial tools on their published changelog. Ranks compare tools within one category and one profile and need at least five measured peers; the overall standing needs three ranked dimensions. Best-in-breed or consolidator is a shape, not a quality, and is never scored.
Release-note detail over time
See how much detail MIND puts in its release notes, quarter by quarter, and compare it with tracked tools in the same category. This history uses up to ten retained, reviewed notes per tool; sparse or blank older quarters may reflect that limit.
Checking release-note history…
Website history
mind.io, every changeMIND's home page and 26 more pages as they looked each month from February 2023 to October 2026: 33 renders, 4 changes of tagline or palette. Step through them, play them, or put any two months side by side.
Website history is included with Researcher and Business.
See plans → Already subscribed? Sign in →← → or h l a month · Shift a year · [ ] previous / next change · Space play · 1 2 3 page · T whole page · C compare · F full size
← → or h l the right month · Shift the left · S swap · W wipe · T whole page · Esc back
Rebranding timeline
Dates bound when a change appeared between captures. Possible rebrands are AI suggestions; a redesign alone does not establish a rebrand.
Releases
4 entries
No entries match these filters.
- September 20263
- July 20261
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