> 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_get_transcript READ # fireflies_get_transcript Retrieves the complete transcript of a Fireflies meeting with speaker attribution and analytics. This is the primary tool for extracting meeting conversation data to create minds or analyze discussions. > **Speaker Email Limitation** > > **Important:** Fireflies does not directly provide speaker email addresses. The MCP server infers emails by correlating speaker names with meeting attendee emails via name matching. For guaranteed accurate speaker emails, use Gong or Fathom. ## 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 ### transcriptId
**Type** string
**Required** Yes
**Description** The unique transcript identifier from `fireflies_list_transcripts` or `fireflies_search_transcripts` response
**Example** `transcript_abc123`
## Request ```json { "transcriptId": "transcript_abc123" } ``` ## Response ```json { "transcriptId": "transcript_abc123", "title": "Weekly Team Standup", "date": "2024-11-15T10:00:00Z", "duration": 1800, "transcript": [ { "speakerName": "Sarah Chen", "speakerEmail": "sarah.chen@company.com", "text": "Good morning team. Let's go around and share our updates for the week.", "timestamp": "00:00:10", "wordCount": 14, "speakingTime": 5 }, { "speakerName": "Mike Johnson", "speakerEmail": "mike.johnson@company.com", "text": "I finished the API integration we discussed last week. It's ready for QA testing now.", "timestamp": "00:00:18", "wordCount": 16, "speakingTime": 6 }, { "speakerName": "Alex Rivera", "speakerEmail": "alex.rivera@company.com", "text": "Great work Mike. I'll start testing that this afternoon. My update is I'm working on the database migration.", "timestamp": "00:00:28", "wordCount": 20, "speakingTime": 8 } ], "speakerAnalytics": [ { "name": "Sarah Chen", "email": "sarah.chen@company.com", "totalSpeakingTime": 360, "wordCount": 720, "talkRatio": 0.20 }, { "name": "Mike Johnson", "email": "mike.johnson@company.com", "totalSpeakingTime": 540, "wordCount": 1080, "talkRatio": 0.30 }, { "name": "Alex Rivera", "email": "alex.rivera@company.com", "totalSpeakingTime": 900, "wordCount": 1800, "talkRatio": 0.50 } ] } ``` ### Response Properties | Property | Type | Description | | -------------------------------------- | ------ | --------------------------------------------------- | | `transcriptId` | string | The transcript identifier | | `title` | string | Meeting title from calendar | | `date` | string | ISO 8601 timestamp of the meeting | | `duration` | number | Meeting duration in seconds | | `transcript` | array | Array of transcript segments in chronological order | | `transcript[].speakerName` | string | Speaker's name | | `transcript[].speakerEmail` | string | Inferred email (via name matching with attendees) | | `transcript[].text` | string | The spoken text for this segment | | `transcript[].timestamp` | string | Timestamp within the meeting (HH:MM:SS format) | | `transcript[].wordCount` | number | Number of words in this segment | | `transcript[].speakingTime` | number | Duration of this segment in seconds | | `speakerAnalytics` | array | Aggregate analytics per speaker | | `speakerAnalytics[].name` | string | Speaker's name | | `speakerAnalytics[].email` | string | Inferred email address | | `speakerAnalytics[].totalSpeakingTime` | number | Total speaking time in seconds | | `speakerAnalytics[].wordCount` | number | Total words spoken | | `speakerAnalytics[].talkRatio` | number | Percentage of total speaking time (0-1) | ## Common Use Cases #### Create Minds from Team Meetings Extract conversation data to train digital minds on team member communication styles. **Example:** ``` "Get the transcript from my standup meeting and create minds for each team member" ``` **Natural language workflow:** 1. Uses `fireflies_list_transcripts` or `fireflies_search_transcripts` to find standup 2. Uses `fireflies_get_transcript` to retrieve full conversation 3. Identifies unique speakers from analytics 4. Creates mind for each speaker 5. Uploads their transcript segments as training data **What you get:** * Minds trained on actual communication patterns * Speaker analytics for each participant * Ability to simulate future discussions * Note: Verify speaker emails due to name-matching inference #### Analyze Speaker Participation Use speaker analytics to understand meeting dynamics. **Example:** ``` "Get speaker analytics from my leadership meetings this month and show me participation patterns" ``` **Natural language workflow:** * Lists leadership meetings * Retrieves transcripts with analytics * Analyzes talk ratios and speaking time * Identifies participation patterns **What you get:** * Detailed speaker metrics * Talk time distribution * Word count analysis * Participation insights #### Training Data Extraction Extract high-quality conversation segments for team training. **Example:** ``` "Get transcripts from my successful client calls and extract the discovery question patterns" ``` **Natural language workflow:** * Identifies successful client calls * Retrieves transcripts * Analyzes question patterns * Extracts effective techniques **What you get:** * Real-world conversation examples * Proven communication techniques * Training materials from actual meetings * Best practice documentation ## Error Responses #### 404 Not Found ```json { "error": "Not Found", "message": "Transcript with ID 'transcript_abc123' does not exist" } ``` **Solution:** Verify the transcript ID is correct. Use `fireflies_list_transcripts` or `fireflies_search_transcripts` to get valid IDs. #### 401 Unauthorized ```json { "error": "Unauthorized", "message": "Fireflies authentication failed" } ``` **Solution:** Verify your Fireflies API key is configured correctly. #### 403 Forbidden ```json { "error": "Forbidden", "message": "You do not have permission to access this transcript" } ``` **Solution:** Check your Fireflies permissions for this meeting. #### 400 Transcript Not Available ```json { "error": "Bad Request", "message": "Transcript not yet available" } ``` **Solution:** Meeting may still be processing. Wait and retry. Check status in Fireflies. ## Best Practices #### Verify Speaker Emails * **Critical:** Speaker emails are inferred, not guaranteed * Review speaker attribution before creating minds * Manually verify emails for important use cases * Consider using Gong or Fathom if accurate emails are required * Check that speaker names match attendee names reasonably well #### Leverage Speaker Analytics * Use talk ratios to find balanced conversations * Identify dominant vs. quiet participants * Select high-engagement meetings for training * Track participation trends over time #### Transcript Processing * Filter to specific speakers when creating individual minds * Use word count to identify substantial segments * Combine transcripts from multiple meetings for richer training * Preserve timestamps for temporal analysis ## Integration with Mind Reasoner ### Creating Minds from Fireflies Transcripts #### Find Meetings Use `fireflies_list_transcripts` or `fireflies_search_transcripts` to find relevant meetings #### Get Transcript Use `fireflies_get_transcript` to retrieve the full conversation with analytics #### Verify Speaker Emails Review inferred speaker emails for accuracy (critical step!) #### Extract Speaker Segments Filter transcript to segments from the target speaker #### Create Mind Use Mind Reasoner's `create_mind` with speaker details #### Upload & Train Upload filtered transcript and create snapshot **Natural language example:** ``` "Find my team meetings from last quarter and create minds for each team member based on their participation" ``` **Important:** The AI will attempt to infer speaker emails, but you should verify the attribution is correct before using minds in production. ## See Also #### [fireflies_list_transcripts](/mcp-tool-fireflies-list-transcripts) Find transcripts before retrieving #### [fireflies_search_transcripts](/mcp-tool-fireflies-search-transcripts) Search transcripts by keyword #### [create_mind](/mcp-tool-create-mind) Create minds from Fireflies transcripts #### [Fireflies Tools Overview](/mcp-integrations-fireflies) See all Fireflies tools and workflows