> This page is for version v8.3.0 (default). > For other versions, use one of these documentation indexes: > - v8.3.0 (default): https://docs.workflows.com/v-8-3-0/llms.txt > For clean Markdown of any page, append .md to the page URL. > For a complete documentation index, see https://docs.workflows.com/llms.txt. > For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.workflows.com/_mcp/server. # fireflies_search_transcripts SEARCH # fireflies_search_transcripts Searches across all Fireflies transcripts by keyword or phrase. This powerful tool lets you discover conversations mentioning specific topics, products, customers, or any other keywords across your entire meeting history. > **Success** > > Fireflies is the only integration that provides native keyword search across transcripts. Use this to find specific topics without knowing dates or participants. ## Prerequisites > **Fireflies Integration Required** > > This tool requires Fireflies integration to be configured. See the [Fireflies Setup Guide](/mcp-integrations-fireflies-setup) for configuration instructions. ## Parameters ### keyword
**Type** string
**Required** Yes
**Description** The keyword or phrase to search for across all transcripts. Supports partial matching and common variations.
**Example** `"pricing objection"` , `"API integration"` , `"enterprise features"`
### fromDate
**Type** string (ISO 8601 date)
**Required** No
**Description** Start date for filtering search results. Format: `YYYY-MM-DD` . If omitted, searches all transcripts.
**Example** `2024-10-01`
### toDate
**Type** string (ISO 8601 date)
**Required** No
**Description** End date for filtering search results. Format: `YYYY-MM-DD` . If omitted, searches up to current date.
**Example** `2024-12-31`
### limit
**Type** number
**Required** No
**Description** Maximum number of results to return. Default: 10. Maximum: 100.
**Example** `25`
## Request ```json { "keyword": "pricing objection", "fromDate": "2024-10-01", "toDate": "2024-12-31", "limit": 25 } ``` ## Response ```json { "results": [ { "transcriptId": "transcript_abc123", "title": "Discovery Call - Enterprise Prospect", "date": "2024-11-15T14:00:00Z", "matchCount": 3, "snippets": [ { "text": "...the biggest concern is pricing. How does your solution compare to the competitors in terms of cost?", "speaker": "Sarah Johnson", "timestamp": "00:15:30" }, { "text": "...I understand the pricing objection. Let me walk you through the ROI calculation...", "speaker": "Mike Chen", "timestamp": "00:15:45" }, { "text": "...so the pricing is actually competitive when you factor in the time savings.", "speaker": "Mike Chen", "timestamp": "00:18:20" } ] }, { "transcriptId": "transcript_def456", "title": "Product Demo - Mid-Market Lead", "date": "2024-11-18T10:00:00Z", "matchCount": 2, "snippets": [ { "text": "...our CFO had a pricing objection last week. Can you explain the value prop more clearly?", "speaker": "Alex Martinez", "timestamp": "00:22:10" } ] } ], "total": 12, "hasMore": false } ``` ### Response Properties | Property | Type | Description | | -------------------------------- | ------- | ------------------------------------------------------ | | `results` | array | Array of search result objects | | `results[].transcriptId` | string | Transcript ID (use with `fireflies_get_transcript`) | | `results[].title` | string | Meeting title | | `results[].date` | string | ISO 8601 timestamp of the meeting | | `results[].matchCount` | number | Number of times the keyword appears in this transcript | | `results[].snippets` | array | Text snippets containing the keyword | | `results[].snippets[].text` | string | Excerpt from transcript with keyword in context | | `results[].snippets[].speaker` | string | Speaker name for this snippet | | `results[].snippets[].timestamp` | string | Timestamp of this snippet (HH:MM:SS) | | `total` | number | Total number of transcripts containing the keyword | | `hasMore` | boolean | Whether there are more results beyond the limit | ## Common Use Cases #### Topic-Based Discovery Find all conversations about a specific topic across your entire meeting history. **Example:** ``` "Search my Fireflies transcripts for all mentions of 'API integration' from the last quarter" ``` **Natural language workflow:** * AI uses `fireflies_search_transcripts` with keyword "API integration" * Filters to Q4 date range * Returns all matching transcripts with context snippets * Shows where and when the topic was discussed **What you get:** * All meetings discussing the topic * Context snippets showing usage * Speaker attribution per mention * Chronological topic tracking #### Customer Feedback Analysis Find customer mentions or feedback across all client conversations. **Example:** ``` "Search for all mentions of 'customer retention' or 'churn' in my client meetings" ``` **Natural language workflow:** * Searches transcripts for keywords * Returns all matching meetings * Shows customer feedback in context * Identifies patterns and trends **What you get:** * Customer sentiment on topics * Feature requests and pain points * Recurring themes * Feedback timeline #### Competitive Intelligence Track competitor mentions across sales conversations. **Example:** ``` "Find all my sales calls where prospects mentioned competitor names" ``` **Natural language workflow:** * Searches for competitor names * Returns relevant conversations * Shows competitive context * Identifies objection patterns **What you get:** * Competitive mention frequency * Context of competitor discussions * Common comparisons * Competitive positioning insights #### Mind Creation from Topics Find conversations about specific topics, then create minds from those discussions. **Example:** ``` "Search for all meetings discussing 'enterprise security', then create minds for the customers who raised those concerns" ``` **Natural language workflow:** 1. Searches for "enterprise security" keyword 2. Retrieves full transcripts for matching meetings 3. Identifies customer speakers from those segments 4. Creates minds for each customer focused on security discussions 5. Trains on their security-related segments **What you get:** * Topic-focused minds * Customer-specific security concerns * Targeted simulation capabilities * Context-aware digital twins ## Error Responses #### 400 Bad Request - Missing Keyword ```json { "error": "Bad Request", "message": "Keyword parameter is required" } ``` **Solution:** Provide a keyword parameter with your search query. #### 401 Unauthorized ```json { "error": "Unauthorized", "message": "Fireflies authentication failed" } ``` **Solution:** Verify your Fireflies API key is configured correctly. #### 429 Rate Limit Exceeded ```json { "error": "Rate Limit Exceeded", "message": "Too many search requests" } ``` **Solution:** Wait before retrying. Reduce search frequency or use more specific keywords. #### No Results Found ```json { "results": [], "total": 0, "hasMore": false } ``` **Solution:** Not an error—no transcripts contain the keyword. Try: * Using different or broader keywords * Checking for typos * Widening the date range * Using partial matches or variations ## Best Practices #### Effective Keywords * Use specific, relevant keywords for best results * Try variations of terms (e.g., "pricing", "price", "cost") * Use phrases for more precise matches (e.g., "enterprise features") * Combine search with date filtering for targeted results #### Search Strategy * Start with broad keywords, then refine * Use date ranges to narrow large result sets * Review snippets before retrieving full transcripts * Save transcript IDs for later retrieval #### Integration with Minds * Search for topics to find relevant conversations * Retrieve full transcripts for matches * Create topic-specific minds from search results * Build knowledge bases around themes #### Performance Tips * Specific keywords return faster than generic ones * Use date filters to reduce search scope * Limit results to only what you need * Review snippets to avoid unnecessary transcript downloads ## Unique Fireflies Capability ### Why Fireflies Search is Special Unlike Gong and Fathom, Fireflies provides **native full-text search** across all transcripts: * **No Date Required:** Find conversations without knowing when they happened * **Topic Discovery:** Uncover forgotten discussions about important topics * **Pattern Recognition:** Identify recurring themes across time * **Contextual Snippets:** See keywords in context before downloading transcripts **Example workflow:** ``` "Find all conversations where we discussed 'enterprise SSO' across my entire Fireflies history, then create minds for the prospects who requested it" ``` This unique capability makes Fireflies ideal for: * Topic-based mind creation * Historical conversation analysis * Feature request tracking * Customer insight mining ## Integration with Mind Reasoner ### Workflow: Topic-Based Mind Creation #### Search by Topic Use `fireflies_search_transcripts` to find all relevant conversations #### Review Snippets Check context snippets to verify relevance #### Get Transcripts Retrieve full transcripts for selected results #### Extract Speakers Identify speakers discussing the topic #### Create Minds Build minds focused on topic-specific communication patterns **Natural language example:** ``` "Search for all discussions about pricing objections, then create a mind trained on how our best reps handle them" ``` ## See Also #### [fireflies_list_transcripts](/mcp-tool-fireflies-list-transcripts) List transcripts by date #### [fireflies_get_transcript](/mcp-tool-fireflies-get-transcript) Retrieve full transcripts from search results #### [Fireflies Tools Overview](/mcp-integrations-fireflies) See all Fireflies tools and workflows