Otter enterprise search expands integrations with MCP to pull Gmail, Drive, Notion and more
Otter enterprise search now connects meeting records with Gmail, Google Drive, Notion, Jira and Salesforce via the Model Context Protocol, enabling unified search and action across workplace apps.
Otter announced a major expansion of its product today as it positions Otter enterprise search to be more than a meeting recorder. The company is launching enterprise search capabilities by adopting the Model Context Protocol (MCP) as a client, a move that lets Otter connect to external services and query that data alongside recorded meetings. The launch allows users to search across Gmail, Google Drive, Notion, Jira and Salesforce, and Otter said Microsoft Outlook, Teams, SharePoint and Slack connections will arrive soon.
Otter adopts MCP to ingest external data
Otter’s implementation of the Model Context Protocol allows the app to pull in context from third‑party sources using a common standard that many AI tools are beginning to adopt. By acting as an MCP client, Otter can treat documents, messages and tickets as searchable context tied directly to meeting transcripts and summaries. The company framed the move as part of a broader strategy to make meeting data actionable rather than simply archived.
The MCP approach is increasingly common among meeting‑focused AI companies that aim to create an integrated workspace, and Otter said the client integrations are designed to reduce the friction of moving information between tools. That change flips the earlier direction of letting outside systems fetch Otter data to instead bringing those external signals into the Otter environment.
Search and actions across Gmail, Drive, Notion and Salesforce
With the new integrations, users can query emails and documents alongside meeting transcripts, and take actions from within Otter based on search results. The product can draft a Gmail message or push a meeting summary directly to a Notion page, enabling workflows that span capture, synthesis and follow‑up without manual copy‑and‑paste. Otter said the initial rollout covers Google services, Notion, Jira and Salesforce, with Microsoft ecosystem support on the roadmap.
The ability to search across disparate repositories is meant to help users find decisions, action items and historical references that live outside a single meeting file. Otter positions these capabilities as an efficiency play for teams that already rely on multiple cloud services to run projects and track work.
Redesigned assistant stays visible and context‑aware
As part of the upgrade, Otter rebuilt its AI assistant to be consistently present across the app interface, allowing users to ask questions at any time. The assistant is designed to interpret the context of the current screen — for example, a specific meeting, channel or document — and return answers that draw on both meeting content and connected external data. That persistent assistant aims to reduce the friction of switching tools when users need quick clarification or to prepare follow‑ups.
Otter said the assistant’s context sensitivity extends to interaction patterns like drafting replies or compiling a summary for distribution, and the company emphasized that the assistant will follow the same privacy and access boundaries as the underlying integrations. The visible presence of the assistant is part of Otter’s push to become a continuous productivity layer rather than an intermittent note taker.
Meeting capture options and the bot vs. botless debate
The industry has been debating two capture approaches: a notetaker bot that joins the call, and botless capture that records system audio on the user’s device. Several competitors have begun offering botless recording modes, and Otter brought a system‑audio capture option to its Mac app late last year. The company is now rolling a similar capability in a Windows app, broadening options for customers who prefer device‑level recording.
Despite adding device audio capture, Otter’s CEO Sam Liang told reporters that enterprise customers generally prefer a notetaker that joins the meeting. Liang said a bot in the call provides clearer transparency and supports sharing notes with all attendees rather than limiting them to an individual. That stance suggests Otter will continue to support both capture models while emphasizing enterprise controls and visibility.
Controls to limit bot proliferation and product safeguards
Otter also introduced practical safeguards to manage notetaker behavior in multi‑participant environments, including a deduplication feature that prevents multiple bots from joining the same call. The company said the measure avoids situations where automated agents outnumber humans on a meeting, a concern for organizations that want clear, accountable meeting participation. These controls reflect a broader emphasis on governance as transcription and summarization tools move into core workflows.
The combination of deduplication and the preference for transparent, shared notes is positioned to address compliance and collaboration concerns for larger customers that demand predictable behavior from meeting agents.
User growth and market positioning amid shifting notetaker landscape
Otter reported that its platform now has 35 million users, up from 25 million users and roughly $100 million in annual recurring revenue reported last year, though the company did not publish updated financial metrics alongside the product announcement. The expansion into enterprise search follows moves by other meeting notetakers that have broadened their feature sets to become fuller productivity platforms.
As notetaker apps push beyond transcription into searchable, integrated workspaces, Otter’s MCP‑based approach aims to place meeting data at the center of decision workflows. The company’s product updates and growing user base position it to compete in a crowded field where integration depth and workplace governance increasingly determine enterprise adoption.
Otter’s extension into enterprise search through MCP and its emphasis on context‑aware assistance signal a shift in how meeting data is used, from passive records to active inputs for team workflows, while the company balances customer preferences for transparency and control with technical options for capture and integration.
