Clarify MCP
Clarify MCP lets agents query and update CRM records, create tasks and lists, analyze pipelines, and work with companies, people, deals, meetings, and campaigns.
Verdict
Common use cases
- Prep for customer calls with conversation history
- Audit deal conversations for objection patterns
- Surface action items from support calls
- Identify coaching moments in rep recordings
- Pull sentiment trends across account touchpoints
Integration
- Vendor
- Clarify MCP
- Category
- other
- Auth
- OAUTH2
- Composio slug
clarify_mcp
Tools
Setup
Setup guide
- 11. Open your Switchy workspace and navigate to Settings > Integrations. 2. Find Clarify MCP in the directory and click Connect. 3. You'll be redirected to Clarify's OAuth consent screen — sign in with your Clarify account. 4. Grant read permissions for conversations, transcripts, and metadata (Clarify will list the exact scopes). 5. After authorizing, you'll return to Switchy and see a green Connected badge next to Clarify MCP. 6. Open any Project and type '@Clarify' followed by a question about a recent call or meeting. 7. If the AI responds with conversation data, the connection is live. 8. To test a specific workflow, try asking '@Clarify summarize the last three sales calls with Acme Corp' and confirm it returns relevant transcripts or insights.
What teammates see: by default, memories from Clarify MCP are scoped to the Project (PROJECT visibility) - you can mark any memory PRIVATE or share it ORG-wide.
Works well with
Top models
Compatibility data appears once enough Projects have used this MCP together with a given model.
How Switchy teams use it
Starter prompts
Pre-Call Research Brief
@Clarify pull the last four conversations with [Account Name] and summarize key topics, open issues, and overall sentiment in bullet points.
Objection Handling Audit
@Clarify find all mentions of pricing or budget concerns in sales calls from the past two weeks and summarize how each rep handled the objection.
Action Item Rollup
@Clarify list all action items and commitments from customer success calls this week, grouped by account.
Deal Risk Check
@Clarify review conversations for [Deal Name] and highlight any red flags like negative sentiment, unresolved concerns, or long gaps between touchpoints.
Coaching Highlight Reel
@Clarify find three examples from this month where reps asked strong discovery questions or turned objections into opportunities, and summarize each moment.
Example outputs
Illustrative - representative of the model's voice and quality, not literal recordings.
@Clarify what are the top 3 user feedback themes from the last 30 days?
Based on recent feedback data, the three most common themes are: (1) Users requesting dark mode support (mentioned in 47 conversations), (2) Confusion about the pricing page layout (32 conversations), and (3) Requests for mobile app notifications (28 conversations). Each theme includes representative quotes and links to the original feedback sessions for context.
This example shows how Clarify surfaces patterns across customer conversations. OAuth2 scope must include read access to feedback data. The MCP aggregates themes automatically, but the quality depends on how feedback is tagged and categorized in your Clarify workspace.
@Clarify create a new insight tagged 'onboarding-friction' linking the 5 conversations where users mentioned setup difficulty
Created insight 'Onboarding friction patterns' with tag 'onboarding-friction'. Linked 5 conversations from the past two weeks where users explicitly mentioned setup challenges. The insight is now visible in your Clarify dashboard under the Onboarding category and will appear in weekly digest reports.
This demonstrates Clarify's ability to organize feedback into actionable insights. Requires write permissions in your OAuth2 scope. The MCP doesn't validate whether the conversations actually contain the described content — you're responsible for accurate linking.
@Clarify pull all feedback mentioning 'API rate limits' and draft a response template addressing the common concerns
Found 12 conversations mentioning API rate limits over the last 60 days. Common concerns: (1) Unclear documentation about limit thresholds, (2) No warning before hitting limits, (3) Confusion between free and paid tier limits. Suggested response template: 'Thanks for the feedback on rate limits. Our [tier] plan includes [X] requests per [timeframe]. You can monitor usage in your dashboard at [link]. If you're hitting limits frequently, we recommend [upgrade path or optimization tip].' Adjust placeholders based on the specific customer's plan.
This example combines Clarify's search with AI synthesis to turn raw feedback into a reusable asset. The template is a starting point — you'll need to customize it per customer. OAuth2 read scope required. Response quality improves when feedback includes structured metadata like plan tier.
Use-case deep-dives
When OAuth overhead pays off for recurring feedback reviews
A 5-person product team runs weekly feedback reviews pulling from Intercom, Zendesk, and user interviews. Clarify MCP uses OAuth2, which means the first setup takes 10 minutes per person but then runs hands-off. If your team reviews feedback once a quarter, that setup cost isn't worth it—export CSVs and use a file MCP instead. But for weekly or daily cadences, OAuth2 wins: no expired API keys, no manual re-auth, and everyone on the team can query the same connected sources without sharing credentials. The trade-off is clear: if you touch customer feedback less than twice a month, skip the OAuth ceremony. If it's a standing meeting, Clarify's auth model saves you from credential drift across the team.
Where Clarify fits in a high-volume support workflow
A 12-person support org handles 400 tickets a week across three products. They need to spot emerging issues before they become fires—think 'login broken on Safari' surfacing from 8 scattered tickets. Clarify MCP is built for this: OAuth2 connects to your ticketing system once, and the MCP can run recurring queries without manual exports. The threshold here is volume and frequency. If you're under 100 tickets a month, a human can scan them faster than setting up an MCP. Above 200, patterns hide in the noise, and Clarify's structured access starts paying rent. The buying call: if your support lead says 'I wish I knew what was trending,' and you're over 150 tickets a month, Clarify is the right scaffold.
When OAuth persistence beats ad-hoc research for market intel
A 3-person go-to-market team tracks competitor moves—pricing changes, feature launches, messaging shifts—across 6 rivals. They used to screenshot and Slack links; now they want a shared workspace that remembers context. Clarify MCP's OAuth2 setup means each team member authenticates once to whatever sources they monitor (G2 reviews, competitor blogs, release notes), and the MCP holds those connections open. The trade-off: if you're doing one-off research sprints, OAuth is overkill—just paste URLs into a chat. But if competitive intel is a standing Monday ritual, OAuth persistence means you're not re-authenticating or re-explaining sources every week. The call: if your team checks competitors more than twice a month, Clarify's auth model turns ad-hoc research into a repeatable workflow.
Frequently asked
What does the Clarify MCP do in Switchy?
The Clarify MCP connects your Switchy workspace to Clarify's time-series data platform. Your team can query sensor data, IoT signals, and industrial metrics directly in AI conversations without switching to the Clarify dashboard. Since no specific tools are documented yet, expect read access to your organisation's signals and basic data retrieval.
Do I need special permissions to connect Clarify via OAuth?
Yes. You'll authenticate through Clarify's OAuth flow, which typically requires at least read access to the signals and data frames your team needs. If your Clarify account has role-based access control, confirm you can view the relevant data sources before connecting. Admin rights aren't usually required unless you're granting workspace-wide access.
Can the Clarify MCP write data or create new signals?
Unknown until the tool list is documented. Most time-series MCPs start read-only for safety — querying existing signals and retrieving historical data. If you need to publish new data points or configure signals, check whether Clarify exposes a write API and whether this MCP implements it. For now, assume read-only access.
Why use this instead of the Clarify web app or REST API?
The MCP lets your team ask questions in plain language and get formatted answers without writing API calls or navigating the Clarify UI. It's faster for ad-hoc queries during meetings or troubleshooting. If you're building automated pipelines or dashboards, the REST API still makes more sense.
Who on the team should connect the Clarify integration?
Whoever owns your Clarify account and understands which signals matter. They'll authenticate once via OAuth, and the connection persists for the whole workspace. If your team shares a service account for integrations, use that. Individual users don't need separate Clarify logins.