Fireflies MCP

Live

OAUTH 2.1

TRANSCRIPTION

Transcription

Every meeting transcript, recording, and AI summary your agent needs to act on lives in Fireflies. Fireflies MCP gives your agent per-user OAuth access to meeting intelligence scoped to the authorizing workspace member.

  • Acts as the user: Transcript access and soundbite creation stay tied to the Fireflies account that authorized the agent.
  • Credentials stay vaulted: AES-256, resolved at request time, never in LLM context.
  • Scoped before every call: User permissions enforced. 90-day audit trail.
Fireflies MCP
agent · Acme Q3
Run
Find all meetings with enterprise customers this quarter and summarize the recurring blockers.
S
fireflies_transcripts_search
198ms
Meeting agent
12 enterprise meetings found. Top recurring blockers: security questionnaire turnaround (8/12 calls), SSO setup complexity (6/12), pricing approval timeline (5/12).
Sources: Fireflies transcripts, Q4 enterprise meetings
firefliesmcp
12
18:29
Message Claude...

Tools your agent reaches for on Fireflies MCP, scoped per user.

CALL ANY TOOL
Search transcripts, retrieve recordings, create soundbites, and access meeting analytics. Same toolkit, every framework, no auth plumbing.
firefliesmcp_fireflies_create_soundbite
Fireflies Create Soundbite
Create a short audio or transcript clip from a meeting recording by specifying start and end times.
Parameters
Name
Type
Required
Description
endTime
number
Required
End time of the soundbite clip in seconds from the beginning of the recording.
startTime
number
Required
Start time of the soundbite clip in seconds from the beginning of the recording.
transcriptId
string
Required
The Fireflies transcript ID of the meeting to clip. Get it from the search or fetch tool.
mediaType
string
Optional
The media type for the soundbite clip (e.g. audio or video).
name
string
Optional
A short label for the soundbite clip.
privacies
array
Optional
Access levels for the soundbite. Pass as a JSON array via the SDK.
summary
string
Optional
A brief description of what this soundbite captures.
firefliesmcp_fireflies_fetch
Fetch fireflies
firefliesmcp_fireflies_get_analytics
Fireflies Get Analytics
firefliesmcp_fireflies_get_channel
Fireflies Get Channel
firefliesmcp_fireflies_get_rule_executions
Fireflies Get Rule Executions
firefliesmcp_fireflies_get_soundbites
Fireflies Get Soundbites
firefliesmcp_fireflies_get_user
Fireflies Get User
firefliesmcp_fireflies_get_user_contacts
Fireflies Get User Contacts
firefliesmcp_fireflies_get_usergroups
Fireflies Get Usergroups
firefliesmcp_fireflies_list_channels
Fireflies List Channels
firefliesmcp_fireflies_move_meeting
Fireflies Move Meeting
firefliesmcp_fireflies_revoke_meeting_access
Fireflies Revoke Meeting Access
firefliesmcp_fireflies_search
Search fireflies
firefliesmcp_fireflies_share_meeting
Fireflies Share Meeting
firefliesmcp_fireflies_update_meeting_privacy
Fireflies Update Meeting Privacy
firefliesmcp_fireflies_update_meeting_title
Fireflies Update Meeting Title
Build your Agent
Drop the toolkit in, point it at the user, and your agent can search Fireflies transcripts and retrieve meeting summaries from the first run.
Python · LlamaIndex
import { ScalekitClient } from "@scalekit-sdk/node";
import { DynamicStructuredTool } from "@langchain/core/tools";
import { createReactAgent } from "@langchain/langgraph/prebuilt";
import { z } from "zod";

const sk = new ScalekitClient(envUrl, clientId, clientSecret);

const { tools } = await sk.tools.listScopedTools("user_123", {
filter: { connectionNames: ["firefliesmcp"], toolNames: ["fireflies_transcripts_search", "fireflies_transcript_get", "fireflies_meetings_list"] },
pageSize: 100,
});

const lcTools = tools.map((t) => new DynamicStructuredTool({
name: t.tool.definition.name,
description: t.tool.definition.description,
schema: z.object({}).passthrough(),
func: async (args) => {
const { data } = await sk.tools.executeTool({
toolName: t.tool.definition.name,
identifier: "user_123",
params: args,
});
return JSON.stringify(data);
},
}));

const agent = createReactAgent({ llm, tools: lcTools });
import { ScalekitClient } from "@scalekit-sdk/node";
import OpenAI from "openai";

const sk = new ScalekitClient(envUrl, clientId, clientSecret);
const openai = new OpenAI();

const { tools } = await sk.tools.listScopedTools("user_123", {
filter: { connectionNames: ["firefliesmcp"], toolNames: ["fireflies_transcripts_search", "fireflies_transcript_get", "fireflies_meetings_list"] },
pageSize: 100,
});

const llmTools = tools.map((t) => ({
type: "function",
function: {
name: t.tool.definition.name,
description: t.tool.definition.description,
parameters: t.tool.definition.input_schema,
},
}));

const resp = await openai.responses.create({
model: "gpt-4o", input: prompt, tools: llmTools,
});
import { ScalekitClient } from "@scalekit-sdk/node";
import Anthropic from "@anthropic-ai/sdk";

const sk = new ScalekitClient(envUrl, clientId, clientSecret);
const anthropic = new Anthropic();

const { tools } = await sk.tools.listScopedTools("user_123", {
filter: { connectionNames: ["firefliesmcp"], toolNames: ["fireflies_transcripts_search", "fireflies_transcript_get", "fireflies_meetings_list"] },
pageSize: 100,
});

const llmTools = tools.map((t) => ({
name: t.tool.definition.name,
description: t.tool.definition.description,
input_schema: t.tool.definition.input_schema,
}));

const msg = await anthropic.messages.create({
model: "claude-sonnet-4-6", max_tokens: 1024,
tools: llmTools,
messages: [{ role: "user", content: prompt }],
});
import { Agent } from "@google/adk/agents";
import {
MCPToolset, StreamableHTTPConnectionParams,
} from "@google/adk/tools/mcp";

const toolset = new MCPToolset({
connectionParams: new StreamableHTTPConnectionParams({
url: "https://mcp.scalekit.com/firefliesmcp",
headers: { Authorization: `Bearer ${userScopedToken}` },
}),
});

const agent = new Agent({
name: "agent", model: "gemini-2.0-flash",
tools: await toolset.getTools(),
});
Try these prompts
Paste any prompt into your meeting agent to start pulling meeting intelligence from Fireflies.
Search & recall
Copy the prompt
Copied
Find all meetings where [topic] was discussed this quarter.
Copy the prompt
Copied
Get the transcript and summary for my meeting with [person] on [date].
Copy the prompt
Copied
List all meetings from the last [N] days.
Action & create
Copy the prompt
Copied
Create a soundbite from the moment [description] in meeting [ID].
Copy the prompt
Copied
Get meeting analytics for my team this month.
Copy the prompt
Copied
Summarize recurring themes across all customer calls this week.
SEE HOW AUTH WORKS
Users authorize Fireflies once. Their workspace credentials stay vaulted, every transcript access is scoped to their account, and every call is logged.
1
Authorize
Your user connects
Fireflies MCP
once. We tie it to their identity and the meetings they approved — no shared bot account, no org-wide access
Who:
user ‘A’
when:
Once per user
access:
Limited to user
2
Store
Their
Fireflies MCP
token lives in a vault scoped to them. User A's meetings are never reachable by an agent acting for user B, even on the same connection
vault:
encrypted
scope:
per-user
tokens:
auto-refreshed
3
Resolve
When your agent calls a
Fireflies MCP
tool, we fetch the right token server-side. It never touches your agent, never appears in the LLM context, never shows up in your logs
speed:
~40ms
check:
before every call
seen by:
nobody
4
Audit
Every
Fireflies MCP
tool call is logged — who triggered it, which meeting was fetched, what came back. 90 days of history, tied to the user who authorized it
history:
90 days
export:
SIEM-ready
logged:
every call
Test other agents
Same per-user auth pattern across other transcription and meeting intelligence connectors.
SALES
Sales call prep agent
Pull Granola notes and Attio contact history to draft a pre-call brief before every sales meeting. Zero rep input.
SALES
Deal intelligence agent
Combine Gong, Attio, and Slack signals to surface deal risks and next-best actions. Updated after every call.
Why Scalekit
Secure your agent's access. Connectors ship in minutes
Other connector libraries treat auth as a demo afterthought. Scalekit starts with user identity, scope enforcement, and audit.
01.
Shared tokens break per-user analytics
A shared token looks fine in a demo. In production every call looks like a service account. Scalekit resolves the real user credential so attribution, audit, and scope stay accurate.
// shared token
 audit → bot_service_account
 user_filter → broken

 // scalekit
 audit → user_abc
 scope → enforced ✓
02.
Authentication is not authorization
03.
Multi-tenancy is architectural
04.
Fireflies MCP today. Others tomorrow.
“Our agents act across Salesforce, Gong, Google Drive, and more, on behalf of every customer. Scalekit behind the scenes meant we can keep adding tools without ever rebuilding how credentials or tool calling work.”
Venu Madhav Kattagoni
Head of Engineering / Von
FAQs
Frequently Asked Questions
Does the agent access Fireflies as the user or a shared account?
As the user. Each workspace member authorizes once and Scalekit resolves their credential. Transcript access is scoped to that user's Fireflies workspace.
Where is the Fireflies OAuth token stored?
In Scalekit's AES-256 vault, namespaced per tenant. Tokens never appear in prompts or LLM context.
Can I prevent the agent from accessing specific meetings?
Yes. Fireflies workspace permissions apply per user. Scalekit enforces credentials and audits all transcript access on top.
What happens when a user revokes Fireflies access?
The connection is invalidated on the next tool call. Subsequent requests fail closed. Other workspace members remain unaffected.
Can the agent create Linear tasks from Fireflies action items?
Yes. A single agent can pull Fireflies action items and create Linear issues in the same workflow, using the same user identity for both connectors.
Start in your coding agent
Up and running in one command
Install the Scalekit skill in your editor of choice. Connector, auth, tools, prompt, all wired up
Claude Code REPL
/plugin marketplace add scalekit-inc/claude-code-authstack
/plugin install agentkit@scalekit-auth-stack
Cursor Code REPL
# ~/.cursor/mcp.json
{
""mcpServers"": {
""firefliesmcp"": {
""url"": ""https://mcp.scalekit.com/firefliesmcp"",
""headers"": { ""Authorization"": ""Bearer $SCALEKIT_TOKEN"" }
}
}
}
Codex Code REPL
# ~/.codex/config.toml
[mcp_servers.firefliesmcp]
url = ""https://mcp.scalekit.com/firefliesmcp""
auth_env = ""SCALEKIT_TOKEN""
Copilot Code REPL
# .vscode/mcp.json
{
""servers"": {
""firefliesmcp"": {
""url"": ""https://mcp.scalekit.com/firefliesmcp"",
""type"": ""http""
}
}
}