Vectara MCP

Provides a bridge between conversational interfaces and Vectara's Retrieval-Augmented Generation capabilities, enabling powerful search queries that return both relevant results and generated responses with customizable parameters.

Skills

Explore the skills and capabilities of this skillset.

ask_vectara

Run a RAG query using Vectara, returning search results with a generated response. Args: query: str, The user query to run - required. corpus_keys: list[str], List of Vectara corpus keys to use for the search - required. Please ask the user to provide one or more corpus keys. api_key: str, The Vectara API key - required. n_sentences_before: int, Number of sentences before the answer to include in the context - optional, default is 2. n_sentences_after: int, Number of sentences after the answer to include in the context - optional, default is 2. lexical_interpolation: float, The amount of lexical interpolation to use - optional, default is 0.005. max_used_search_results: int, The maximum number of search results to use - optional, default is 10. generation_preset_name: str, The name of the generation preset to use - optional, default is "vectara-summary-table-md-query-ext-jan-2025-gpt-4o". response_language: str, The language of the response - optional, default is "eng". Returns: The response from Vectara, including the generated answer and the search results.

search_vectara

Run a semantic search query using Vectara, without generation. Args: query: str, The user query to run - required. corpus_keys: list[str], List of Vectara corpus keys to use for the search - required. Please ask the user to provide one or more corpus keys. api_key: str, The Vectara API key - required. n_sentences_before: int, Number of sentences before the answer to include in the context - optional, default is 2. n_sentences_after: int, Number of sentences after the answer to include in the context - optional, default is 2. lexical_interpolation: float, The amount of lexical interpolation to use - optional, default is 0.005. Returns: The response from Vectara, including the matching search results.

Configuration

Customize the skillset to fit your needs.
MCP Server

Connect to MCP Server

Vectara MCP

Office Docs Helper
An AI-powered virtual administrative assistant for internal company operations. Helps you quickly create high-quality internal documents like announcements, meeting minutes, summaries, forms, procedures, and HR records.
AI Programmer
AI Programmer is an AI agent that transforms your raw release notes into stylish, ready-to-publish HTML pages.
AI Writer
Tell me about the AI product or brand — I’ll draft engaging marketing copy, articles, and social media posts tailored to your brand voice and product details, complete with relevant links and illustrations.
Community Reporter
Analyze community screenshots and report engagement trends and discussion highlights. Upload a screenshot of your community interactions, and the agent generates a clear markdown report summarizing engagement levels, key discussion topics, and notable highlights — perfect for community managers, marketers, and product teams.
Customer Support Scribe
An AI assistant that helps customer support teams create high-quality support documentation, including FAQs, ticket replies, apology letters, and SOPs. Guides you through creating both internal resources and customer-facing materials.
Email Marketer
Finds leads and sends a 3-day follow-up email sequence automatically.
X/Twitter Manager
An AI-powered Twitter Assistant that helps content creators turn AI product experiences into viral tweets — with auto-polish, smart research, and one-click posting.
Google Analyst
Step-by-step guide to connect your Google Analytics 4 (GA4) property to the Google Analyst agent. Covers creating a Google Cloud service account, enabling the Analytics Data API, granting GA4 Viewer access, and configuring the agent with supported metrics like sessions, users, bounce rate, conversions, and more. Perfect for quickly setting up GA4 data reporting in Bika.ai.
Requirements Document Writer
Tell me about your product or feature idea — I'll help you create comprehensive and detailed requirements documents that cover user stories, acceptance criteria, technical specifications, and more.

Frequently Asked Questions

Quick one-sentence introduction: What is Bika.ai?
What make Bika.ai so unique?
The English abbreviation "BIKA" stands for what meaning?
How does Bika.ai automate tasks with AI?
Is Bika.ai free to use?
What is the difference between Bika.ai and AI assistants like ChatGPT, Gemini?
What is the difference between Bika.ai and spreadsheet database?
Does Bika.ai get poor performance when the single database records reaches tens of thousands or hundreds of thousands of rows and the associations become more complex?
What is the 'Space' in Bika.ai?
How many paid spaces do I own after making a payment?
What does 'Resources' mean?
How does the Bika.ai team 'eat your own dog food' (use their own product)?
How does Bika.ai help improve work efficiency?
What are the features of Bika.ai's AI automation?
What are the automation templates in Bika.ai?
Does Bika.ai support team collaboration and permissions features?

Embark on Your AI Automation