Connect your AI tools to ChronoTracer
Today we are introducing ChronoTracer MCP. ChronoTracer MCP lets the AI tools your team already uses query ChronoTracer’s organized record of your case evidence, helping them produce more accurate and more comprehensive answers than they can from raw files alone, even across matters involving millions of records.
Raw files leave gaps in AI answers
Ask an AI platform a question about your case, and you can get a confident answer in seconds. The real question is whether that answer is accurate and comprehensive.
Answering a question like “What did she do in the week after the wire transfer?” means finding every related fact across emails, texts, calls, payments, meetings, and other evidence.
Working from raw files, even capable AI platforms can miss important parts of the record, and not just on big cases. They often struggle with event-heavy evidence like phone records and system logs. They can miss sequences of activity spread across different documents. And they may fail to connect a person’s phone numbers, email addresses, and account handles, leaving part of that person’s activity unseen.
The answer looks complete. It often is not.
For many case questions, the limiting factor is not the AI model. It is whether the model has a reliable, organized representation of what happened.
ChronoTracer gives AI a structured record of the evidence
ChronoTracer organizes case evidence into individual events: an email sent, a text exchanged, a call placed, a payment made, a meeting held. Those events are deduplicated, placed in time order, connected to the people involved, and linked back to their source documents.
Core events are extracted from the evidence using purpose-built software rather than generated by an AI model. The same source evidence produces the same core events, giving your AI a consistent, reproducible, and auditable foundation to work from.
In March, we introduced ChronoTracer’s built-in AI assistant, which answers questions by querying that structured record and returning the underlying events with source citations. ChronoTracer MCP opens the same record to your other AI tools.
It is built on the Model Context Protocol, or MCP, an open standard for connecting AI systems to outside data and tools. ChronoTracer MCP is designed to work with MCP-compatible AI assistants and agents, including Claude, ChatGPT, Gemini, Microsoft Copilot, and legal AI platforms adopting MCP.
Get more complete answers, faster
When your AI queries ChronoTracer instead of working directly from raw files:
- Answers are more accurate and more comprehensive. Your AI can retrieve related facts together even when they span an email, several texts, a phone record, a financial transaction, and a translated document. Phone records and logs are already part of the record, and phone numbers, email addresses, and account handles are already connected to the people who use them. The events ChronoTracer returns come directly from the structured case record and include source citations, rather than being generated text, so claims in your AI’s answer can be checked directly against the evidence.
- Answers come faster. Instead of searching and loading large numbers of source documents, your AI can ask ChronoTracer for exactly what it needs: a date range, a person, a set of communications, or a sequence of events. Less time finding the evidence means more time analyzing it.
- Built for litigation scale. Large litigation records cannot simply be loaded into an AI’s context window. ChronoTracer lets your AI query the relevant parts instead, using the same approach whether a matter contains thousands of events or the tens of millions ChronoTracer has processed on its largest matters.
Combine the evidence with the rest of your case
This is more than moving ChronoTracer’s questions into another interface. Your AI platform may already have access to your legal research, draft briefs, memos, pleadings, deposition summaries, and other case materials. ChronoTracer MCP adds a structured view of the evidence to that existing context.
Your AI can use what it already knows about the matter to ask better questions of the evidence, then combine ChronoTracer’s structured event data with the legal and factual context it already has. ChronoTracer does not need to recreate that context inside its own application.
For example, with those materials in your AI’s context, your team can ask:
- “Identify gaps in Brett Boston’s phone record production and assess whether they affect the argument in our draft motion.”
- “Show all calls, texts, emails, and financial transactions involving the CFO in the two weeks before the merger announcement, and compare them with the timeline alleged in the complaint.”
- “Show events involving board members within 24 hours after the Fall 2023 board meeting and identify anything relevant to the issues in our investigation memo.”
- “Find communications involving Patricia Vance in the week before closing that bear on the knowledge issue identified in our deposition outline.”
Use ChronoTracer in the AI tools your team already knows
ChronoTracer MCP brings the organized case record into the AI tools your team already uses, while keeping ChronoTracer’s web application available when you want to explore the evidence directly. Your team can move easily between AI analysis and the underlying structured record without recreating its broader case context inside ChronoTracer.
ChronoTracer is delivered as a white-glove managed service, so getting started means loading evidence, not running an IT project. Each matter runs in its own isolated, single-tenant environment. ChronoTracer has successfully completed a SOC 2 Type II examination conducted by an independent third-party auditor, with no exceptions noted.
If you would like to see what your AI tools can do with organized evidence, schedule a demo and we will walk you through it.