Locate functions, classes, and files matching a natural language description to understand where functionality lives and avoid duplicating existing code.
MIT
457,771 tools. Updated 2026-08-14 15:09
"Adding functionality to large language models" matching MCP tools:
- Search SFRA documentation to find implementation details for controllers, models, routing, middleware, cart functionality, and customer management.MIT
- Generate machine-readable permission guidelines for AI models by creating standardized llms.txt files that define how large language models should interact with websites.MIT
- Generate a standardized llms.txt file that defines how large language models interact with your website. Specify allowed URLs and permissions for AI agents.MIT
- Generate machine-readable permission guidelines for AI models by creating standardized LLMs.txt files that define how large language models should interact with websites.MIT
- Retrieve SFRA documentation filtered by functional categories like core classes, product models, order/cart functionality, customer management, pricing, or store models to explore related documentation and understand functional groupings.MIT
Matching MCP Servers
- AlicenseAqualityCmaintenanceClassifies development task complexity (LIGHT/MEDIUM/HEAVY) and recommends the most cost-efficient AI model per provider, enabling optimized model selection for coding tasks.319MIT
- AlicenseAqualityCmaintenanceEnables downloading real binary files from Egnyte and uploading large files with chunked support, complementing the official Egnyte MCP connector.5Apache 2.0
Matching MCP Connectors
27 verified financial calculators with published specs; responses cite assumptions and sources.
Transform any blog post or article URL into ready-to-post social media content for Twitter/X threads, LinkedIn posts, Instagram captions, Facebook posts, and email newsletters. Pay-per-event: $0.07 for all 5 platforms, $0.03 for single platform.
- Find existing memories by natural language queries to avoid duplicate entries. Search before adding new information.Apache 2.0
- Query your API graph with natural language to find routes, models, and middleware. Identify unprotected routes or unused models.MIT
- Delete a Cognigy.AI NLU connector. Use dryRun=false to confirm deletion; endpoints using this connector will lose NLU functionality.MIT
- Search Gene Ontology Causal Activity Models (GO-CAMs) by title, state, contributor, group, publication, or gene product to find specific models with metadata.BSD 3-Clause
- Create new content entries in Contentrain CMS with automatic system field generation, supporting localized models and draft/publish status management.
- Discover available LLM models for brand monitoring. Use to select specific models before creating a project or running a scan.MIT
- Delete a Cognigy.AI large language model configuration. Features using this model stop working. Use dryRun parameter to validate before deletion.MIT
- Browse registered generation models to see names, IDs, target LLM configs, and creation timestamps. Identify available models for testing.Apache 2.0
- Test the connection to a Cognigy.AI large language model provider to validate credentials and reachability before using it in flows.MIT
- List available voices for AI agents, returning voice IDs, gender, language, and supported models to help configure an agent's voice.MIT
- Lists large language model configurations for Cognigy.AI generative AI features like Knowledge AI and AI Agents, showing provider, model type, and connection info, with pagination and filtering options.MIT
- Retrieves detailed configuration of a specific large language model, including provider settings, model type, connection details, and fallback configuration.MIT
- List available AI models with pricing to discover options and compare costs.MIT
- Find alternative packages for your npm dependencies. Compare similar functionality to identify suitable replacements.TypeScriptMIT