• ERROR DETECTION
  • DATA QUALITY
  • USER FEEDBACK
  • HUMAN REVIEW

How to audit RAG chat history with your AI

Connect Vectara to your AI client to pull past sessions. Once connected, your agent can scan through previous interactions to find errors or verify facts.

Ask AI about this page

Short answer

How can I audit my RAG chat history?

Your AI uses the Vectara MCP to pull a list of your previous chat sessions. You can then ask your agent to analyze these specific sessions for accuracy or context errors. This allows you to spot where your RAG implementation might be failing.

Audit outcomes

Where your findings land

What you get after your AI scans your history.

ERROR DETECTION

Find hallucinations

Your AI reviews past answers against the original grounded data. It flags where the model strayed from the provided context.

DATA QUALITY

Check retrieval accuracy

The agent looks at which documents were pulled for specific questions. This helps you see if the right information is actually being found.

USER FEEDBACK

Review session trends

Your AI identifies patterns in how users interact with your RAG setup. You'll see which topics cause the most confusion or incorrect answers.

HUMAN REVIEW

Identify manual fixes

The AI highlights specific sessions that need a human to step in. You'll know exactly which chat logs require manual correction or better grounding.

The workflow

What your AI does when the request arrives.

The AI handles the data retrieval so you can focus on the analysis.

  1. Fetch session logs

    The agent reaches into Vectara to pull a list of all recent chat interactions. This provides the raw material for your audit.

    list_chat_sessions

  2. Isolate specific chats

    Your AI filters through the session list to find the exact conversations you want to inspect. It targets specific timeframes or session IDs.

    list_chat_sessions

  3. Analyze grounding

    The agent compares the chat responses to the retrieved context. It looks for discrepancies between what was said and what the data supported.

    list_chat_sessions

  4. Summarize findings

    Your AI compiles the errors or successes it found into a readable report. You get a clear view of your RAG performance.

    list_chat_sessions

Try it

Copy these to start.

Use these prompts to begin your audit.

Starting points

These are opening lines. Swap out the session IDs or dates with your actual Vectara data.

Vectara Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_P55Xdk6UU5XMN3cdVPORquufduaGCfpEWSemsNQg/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Vectara capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "vectara-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_P55Xdk6UU5XMN3cdVPORquufduaGCfpEWSemsNQg/mcp"
    }
  }
}
Copy into chat04

  • List my recent Vectara chat sessions so I can pick one to audit.

  • Look at the last five chat sessions from Vectara and tell me if any of them hallucinated.

  • Find the chat session from yesterday and check if the retrieved context actually supported the answer.

  • Review my Vectara chat history and summarize the most common reasons for incorrect answers.

  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Start here

Connect Vectara once, then ask.

Just click the link to connect your account. Your credentials stay encrypted, and you can immediately start asking your AI about your chat logs.

Connect Vectara to your AI

FAQ

How this task behaves

  • 01

    Can the AI delete chat sessions in Vectara?

    No. The AI can only list and read existing sessions to perform the audit.

  • 02

    Can my AI change the answers in my chat history?

    No. The AI can analyze the history, but it cannot modify or rewrite the logs stored in Vectara.

  • 03

    How does the AI know if an answer was a hallucination?

    The AI compares the chat response against the specific context retrieved during that session to see if the facts align.

  • 04

    Does the AI see all my data or just chat history?

    Through this specific MCP, the AI only accesses the chat session data provided by the list_chat_sessions tool.

  • 05

    Can I audit sessions from a different user?

    The AI can only access the sessions that your connected Vectara account has permission to view.

  • More questions about Vectara? The Connector page answers them. See everything the Vectara Connector can do

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