# Investigate an MCP search with no matches before changing a pack Canonical: https://opendataroom.com/guides/no-match-mcp-request-triage Updated: 2026-10-17 Investigate why a literal MCP search returned no matches. Keep the relevant documents in OpenDataRoom, then let your own or the recipient’s compatible AI work from that selected evidence. You choose the sources, access and sharing window. ## How OpenDataRoom helps Market: Fundraising, investor-relations and information-pack owners Investigate why a literal MCP search returned no matches. Keep source documents organised in drops, like folders, and select named packs for each audience. OpenDataRoom manages access and request records; the recipient uses their own AI for analysis. Current AI tools return extracted text, not complete original files. - [MCP request ledger](/guides/mcp-request-ledger): Review requests received through an authorised connection and what the service prepared, without claiming visibility into the full conversation. - [Source access for your AI](/guides/ai-document-connection): Let a compatible AI list, search and read the supplied text. Ask it to cite the file and passage so you can check the answer. ### Workflow impact A retry plan that separates wording, extraction and scope problems. The reviewer can consult the selected evidence through one authorised connection, then check and use the result in their existing workflow. ### Bring these documents - Search result note.md ### Prompt for your own compatible AI Using only this approved pack, investigate why a literal MCP search returned no matches. Start with this source question: Does the first no-match mean the owner lacks market-sizing information? Cite the file and passage. Distinguish supplied facts, assumptions, missing evidence and contrary evidence. Do not infer human reading or investment intent from request records. Review the AI draft against the originals, resolve open questions with the document owner, and take the checked result into your own meeting, report or customer response. ## Frequently asked questions ### What would this change in my workflow? A retry plan that separates wording, extraction and scope problems. The reviewer can consult the selected evidence through one authorised connection, then check and use the result in their existing workflow. The practical task is to investigate why a literal MCP search returned no matches. ### Which documents should I include? For the example on this page, start with Search result note.md. Use the approved versions relevant to the task and include source dates, definitions and any known gaps. Review the prepared text and disclosure scope before sharing. The fictional examples illustrate the structure; OpenDataRoom does not supply or verify your underlying research. ### Can the ledger tell me whether an investor intends to proceed? It can show the tool requests received through an authorised connection, the source references requested and the response preparation outcomes. Those records can inform a useful clarification or follow-up. They do not prove that the investor personally read a result, that an AI relied on it, or that an investment decision was made. An AI app may issue several requests automatically. ### How does the recipient connect, and who gets access? Choose your own AI or invite the intended email recipient. For a private invitation, the recipient verifies the authorised email and completes the required approval flow, then adds the connection in a compatible AI app’s settings. Forwarding an invitation alone does not authorise a different email. Permission covers the selected pack; create separate packs when audiences may see different documents. ### Can I keep the files and end someone’s access? Your wallet contains source drops, like folders. Each named pack shares selected files or passages from one drop. The source drop and its access packs have separate deadlines. You can keep the source until its displayed retention deadline while ending a recipient’s future access. Choose a sharing window, revoke it earlier when needed, and approve an extension deliberately. Expiry cannot recall material that an AI app or recipient has already retrieved. ### What happens when I update or remove a file? After you review and accept a drop update, fresh authorised requests receive the current versions of files already selected for their packs. This does not force an AI to fetch the files again or refresh its existing chat context. New files do not join those packs automatically. Review changed selected passages explicitly. Removing a file or its permission stops future retrieval, and access-change notices are queued for affected recipients. Provider acceptance is not proof of inbox delivery. This cannot erase content already retrieved. ### What if my files or AI app are not supported? Check the compatibility guide and try the public service-information sample first. An app must support the required MCP connection and authorisation; pasting a URL into ordinary chat does not install it. Use supported text-based files and inspect the preparation report. Originals are retained in encrypted storage, but the current AI tools return extracted text, not complete original files. Charts, images and layout are not faithfully delivered by those tools. Image-only scans and standalone images are refused; no OCR, audio transcription or spreadsheet recalculation is provided. Current pilot limits are listed on the pricing page. ### What information is recorded about use of the pack? The ledger records requests received by the service, authorised connection references, requested source information and preparation outcomes. Recipients can also deliberately submit a request, comment or note after approving the exact text. The owner sees that message, the verified connection identity and time in Recipient inbox for up to 90 days, unless deleted sooner. Received does not mean read or answered; no agent or automatic research is started. It does not record the entire AI conversation. Search text is supplied by the AI and may differ from the human question. An AI can reuse retrieved material without making another request. Literal search can miss relevant material; neither a search nor a file request proves that the AI reviewed the entire pack. Owners can investigate no-match searches before deciding whether to clarify wording, repair extraction or add information. A no-match result alone is not proof that a document is missing. ### Who can read my files in the hosted connection? Private-library file names and contents are encrypted in the browser with your wallet key. A hosted AI connection uses a separate access copy that you approve and that the service can decrypt for authorised retrieval. The receiving AI gets the content it retrieves and applies its own data policies. An optional desktop connector can decrypt locally, but it requires installation and is not a universal mobile connection. Review the security and compatibility pages before choosing a route. ## Your working output A retry plan that separates wording, extraction and scope problems ## Before you share 1. Bring the approved, dated versions of: Search result note.md. 2. Check the readable text, source dates and permitted audience. 3. Choose your own compatible AI or invite the intended recipient with an appropriate access deadline. 4. Check the result against the source before using it; retain open questions rather than filling gaps. ## Fictional example documents These are invented teaching documents, not customer evidence. ### Search result note.md Fictional note: total addressable market assumes 10,000 organisations at £1,000 annually. The abbreviation searched in the example does not occur in this sentence. ## A source question Does the first no-match mean the owner lacks market-sizing information? Illustrative answer: No. In this fictional example the full phrase is present. Literal wording explains the first no-match. In a real case incomplete extraction or absent source evidence remain alternatives to check. ## Sources and further reading ## Related workflows - https://opendataroom.com/guides/no-match-search-what-it-means - https://opendataroom.com/guides/adviser-review-source-independence-check - https://opendataroom.com/guides/ai-answer-provenance-for-reviewers Admission is by invitation. Join the waiting list: https://opendataroom.com/signup Check compatibility and the separate public service-information sample: https://opendataroom.com/compatibility ## Try the fictional example https://opendataroom.com/example-demo.html?example=no-match-mcp-request-triage