For AI agents: a documentation index is available at the root level at /llms.txt and /llms-full.txt. Append /llms.txt to any URL for a page-level index, or .md for the markdown version of any page.
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HomeDocsAPI ReferenceMCP ServerChat SDKsRelease Notes
HomeDocsAPI ReferenceMCP ServerChat SDKsRelease Notes
  • Introduction
    • Overview
    • Getting started
    • Authentication
    • Data privacy
    • Built-in prompts
    • FAQ
    • Troubleshooting
  • Tools
    • Overview
    • get_ada_configuration
    • get_ada_metric
    • get_available_filters
    • get_conversations
    • get_conversation
    • search_knowledge
    • search_coaching
    • get_improvement_guide
    • list_entities
    • propose_change
    • get_test_cases
    • get_test_runs
    • get_test_run_quota
    • send_feedback
  • Prompt library
    • Overview
    • Improvement recommendations
    • Quick health checks
    • Create visualizations
    • Diagnose performance issues
    • Identify optimization opportunities
    • Review configuration
    • Search knowledge and coaching
    • Test agent responses
    • Deep-dive analysis
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On this page
  • Tool index
  • Configuration
  • Metrics and conversations
  • Knowledge and coaching
  • Entity discovery
  • Testing
  • Writes
  • Feedback
  • Typical call patterns
Tools

Tools overview

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get_ada_configuration

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The MCP server exposes a set of tools that your AI assistant (Claude, ChatGPT, Gemini, etc.) can call to read Agent configuration, query metrics, pull conversation data, manage test cases and test runs, and propose changes to resources (knowledge articles, custom instructions, test cases). Each tool page documents parameters, response shape, and example usage.

Tool index

Configuration

ToolWhat it does
get_ada_configurationFetches playbooks (summary), actions, custom instructions, and company description.

Metrics and conversations

ToolWhat it does
get_ada_metricReturns AR rate, CSAT, containment, and engaged conversation volume with conversation-level metadata.
get_available_filtersLists supported filter types and operators for conversation queries.
get_conversationsReturns many conversations at IDS_ONLY or SUMMARY detail.
get_conversationReturns the full transcript for a conversation ID.

Knowledge and coaching

ToolWhat it does
search_knowledgeSearches existing knowledge articles.
search_coachingSearches existing coaching entries.
get_improvement_guideReturns Ada’s entity improvement guide and best practices. Call before proposing changes.

Entity discovery

ToolWhat it does
list_entitiesLists channels, topics, variables, playbooks, or handoffs configured for the Agent.

Testing

ToolWhat it does
get_test_casesRetrieves test cases, optionally filtered by name or grouped by channel.
get_test_runsRetrieves test run results, pass/fail status, and evaluation rationale.
get_test_run_quotaReturns daily test run quota, usage, and remaining runs.

Writes

ToolWhat it does
propose_changeCreates, updates, or deletes knowledge articles, custom instructions, and test cases, and triggers test runs through a three-phase discover → preview → confirm flow.

Feedback

ToolWhat it does
send_feedbackSends structured feedback directly to Ada’s development team when MCP tools are blocked, unclear, or missing capabilities.

Typical call patterns

  • Performance analysis: get_available_filters → get_conversations → get_conversation (for selected IDs) → get_ada_metric for aggregates.
  • Configuration review: get_ada_configuration → search_knowledge / search_coaching to cross-reference existing content.
  • Improvement recommendations: get_improvement_guide → get_ada_metric (to find under-performing conversations) → get_conversation (for transcripts) → get_ada_configuration (to identify gaps) → search_knowledge / search_coaching → propose_change to create or update entities.
  • Test-driven development: get_conversations (production samples) → propose_change with test_case → propose_change with test_run → get_test_runs to review results.