Bland AI

@bland-ai list all calls from the past 7 days and show me which ones had a successful transfer

Found 23 calls in the past week. 8 calls successfully transferred to a human agent, 12 completed without transfer, and 3 were dropped before completion. The highest transfer rate occurred on Tuesday afternoon (5 of 7 calls). Most successful transfers happened when the caller asked for billing questions or technical support beyond the agent's scope. Average call duration before transfer was 2.3 minutes.

This example showcases the call history search capability. The MCP returns structured call metadata including outcomes and transfer events. Note that call recordings and transcripts are not included in the list response — you'd need separate tool calls to retrieve those. API key must have read access to call logs.

@bland-ai create a new pathway folder called 'Q1 Sales Campaigns' under the existing 'Outbound' folder

Created pathway folder 'Q1 Sales Campaigns' with ID pf_8k2m9n4p. The folder is now nested under 'Outbound' (pf_3j7h5k1m) and ready to organize pathways. The folder is currently empty — you can move existing pathways into it or create new ones directly inside. Folder appears in the US regional pathway service and is visible to all team members with pathway access.

This demonstrates the organizational tooling for conversational pathways. The MCP confirms the folder creation and returns its ID for subsequent operations. Remember that Bland AI requires folders to be empty before deletion, so plan your hierarchy carefully. This is a write operation that immediately affects your account structure.

@bland-ai check my account balance and tell me if I have enough credits to run 500 outbound calls this week

Your Bland AI account currently has 1,247 call credits remaining with auto-refill enabled at 200 credits. Based on your average call duration of 3.2 minutes and current per-minute rate, 500 calls would consume approximately 1,600 credits. You're 353 credits short. However, with auto-refill triggering twice during the week (at current usage pace), you should have sufficient credits by mid-week. Consider manually adding credits if you need to front-load the campaign.

This example pairs the account details tool with AI reasoning to answer a planning question. The MCP provides raw account data (balance, refill settings, call history stats), and the AI performs the capacity calculation. Useful for budget forecasting before launching campaigns. Requires API key with account-level read permissions.

When Bland AI fits a 2-person SDR team doing cold outreach

A two-person SDR team running 40 cold calls a day needs a shared view of what happened on each dial. The List Calls tool pulls transcripts and outcomes into Switchy so both reps see who picked up, who asked for a callback, and who hung up in five seconds. The Get Account Details tool surfaces your monthly balance so you know when to top up credits before a big push. This works if your reps are already comfortable with Bland's voice agent setup and you just need the call history in one place. If you're still experimenting with scripts or pathway logic, you'll spend more time in Bland's own dashboard than in Switchy. Buy this integration when your call volume is steady and you want the team to review outcomes together without switching tabs.

Why support teams use this MCP to audit AI agent training data

A four-person support team runs a Bland voice agent that answers tier-one questions about shipping and returns. The List Knowledge Bases tool shows which PDFs and help articles the agent is trained on, plus their processing status. When a customer complains the bot gave outdated info, the team pulls the knowledge base list into Switchy, spots the stale file, and flags it for refresh. The List Contacts tool surfaces which customers have called before and what the agent remembered from past conversations. This scenario works if you already have a Bland agent live and you need a quick audit layer. If you're still building the knowledge base or the agent isn't deployed, you'll get more value from Bland's native interface. Use this integration when your agent is in production and you want the team to spot training gaps fast.

When pathway folders help a product team test call flows

A three-person product team is A/B testing two versions of a sales qualification flow in Bland. The Create Pathway Folder and List Pathways tools let them organize test variants in Switchy without cluttering Bland's main workspace. One folder holds the control flow, another holds the experimental branch with an extra objection-handling node. The team reviews node-by-node logic in Switchy during sprint planning, then pushes changes back to Bland when they pick a winner. This works if your team is iterating on call scripts weekly and you want a shared changelog. If you only have one pathway or you rarely touch the flow, the folder overhead isn't worth it. Buy this integration when you're running multiple pathway experiments and you need the team to compare versions side by side.