List all MCU targets supported by pyocd, including over 206 built-in targets from vendors like STM32, NXP, Nordic. Search by name with filter_text.
MIT
307,703 tools. Last updated 2026-07-18 18:18
"NXP" matching MCP tools:
- Execute TypeScript code with automatic tool discovery and parameter mapping using ncp.do().Elastic 2.0
- Count paragraphs in text by detecting blank line separators. Analyze document structure and assess text segmentation for NLP tasks.MIT
- Split text into word tokens, handling contractions, hyphenated words, numbers, and punctuation.MIT
- Retrieve schema details for any Snowflake table by providing its fully qualified name. Get column names, data types, and constraints.MIT
- Split text into sentences by accurately handling abbreviations like Mr. and Dr. and complex boundary conditions, ensuring reliable sentence segmentation.MIT
Matching MCP Servers
- AlicenseAqualityCmaintenanceUnified MCP orchestration layer that consolidates multiple MCPs into a single interface with semantic tool discovery, code-mode execution, scheduling, and intelligent caching to reduce token usage by 97% and eliminate choice paralysis.Last updated213096Elastic 2.0
- AlicenseBqualityDmaintenanceEnables AI assistants to manage Optimizely DXP deployments through natural language conversations. Supports code deployment, database operations, content synchronization, and environment management across Integration, Preproduction, and Production environments.Last updated42692MIT
Matching MCP Connectors
Connect your XP account to AI via Brazil's Open Finance: balances, statements, cards, investments. R
Narodowy Bank Polski (National Bank of Poland) Web API MCP. Keyless.
- Extract key sentences from text to generate a concise summary. Scoring considers sentence position, keyword frequency, length, and title overlap for relevance.MIT
- Analyze each sentence in a text to retrieve sentiment scores and labels, offering granular understanding of emotional tone across sentences.MIT
- Extract sentiment scores for specified aspects in text by detecting related sentences and computing average sentiment.MIT
- Remove all punctuation from text to produce clean, normalized output for downstream NLP tasks.MIT
- Search for MCP tools by capability description or list all available tools. Use pipe separator for multi-query searches.Elastic 2.0
- Compute normalized edit distance between two strings on a 0–1 scale, where 0 means identical and 1 means completely different. Provides a measure of string similarity suitable for comparing text.MIT
- Reduce English words to their base stem using the Porter stemming algorithm. Input a word and get its stem, e.g., 'running' becomes 'run'.MIT
- Clean text by removing HTML, URLs, emails, numbers, punctuation, stopwords, extra whitespace, and converting to lowercase. Configurable pipeline selects which cleaning steps to apply.MIT
- Estimate syllable count for any word using heuristic rules. Helps assess readability, poetic meter, or pronunciation difficulty.MIT
- Compute TF-IDF from scratch to extract key terms from a set of documents. Provide multiple documents for improved keyword relevance scoring.MIT
- Calculate the Levenshtein edit distance between two strings, returning the minimum number of single-character edits needed to transform one string into another.MIT
- Generate n-grams from a list of tokens for text analysis. Returns a list of n-gram lists, useful for language modeling and feature extraction.MIT
- Estimate the formal education years needed to understand a given text, providing a readability score for content analysis.MIT
- Calculate the SMOG grade index for healthcare and medical texts by counting polysyllabic words to assess readability.MIT