Rosette Text Analytics MCP server

Connect Rosette Text Analytics to Claude, ChatGPT, Cursor, Claude Code, Codex, Gemini, GitHub Copilot and any other MCP client, for your whole team. Metorial adds security, governance, and tracing, and gives everyone one Magic MCP URL to connect.

What you can do with the Rosette Text Analytics MCP server

Ask your agent in plain language. Each of these maps to a real tool on the server.

  • Use the transliterate text tool in Rosette Text Analytics
  • Use the analyze sentiment tool in Rosette Text Analytics
  • Use the analyze morphology tool in Rosette Text Analytics
  • Use the detect language tool in Rosette Text Analytics
  • Use the translate name tool in Rosette Text Analytics
  • Use the compare addresses tool in Rosette Text Analytics

Supported Tools

transliterate_text

Transliterate Text

Transliterates Arabizi or Romanized Arabic chat text into native Arabic script. Use translate_name for translating names between other supported languages and scripts.

analyze_sentiment

Analyze Sentiment

Determines sentiment in text at the document level and optionally at the entity level. Returns sentiment labels (pos, neu, neg) with confidence scores. Entity-level analysis identifies entities and determines the sentiment expressed toward each one.

analyze_morphology

Analyze Morphology

Performs morphological analysis on text, returning part of speech tags, lemmas (dictionary form), compound components, and Han readings for each token. Can return all features at once or individual features.

detect_language

Detect Language

Identifies the language of a given text across supported languages. Can optionally use multilingual detection mode to identify language regions within the same document, useful when text contains multiple languages. Use list_supported_languages to discover language availability.

translate_name

Translate Name

Translates a name from one language to another, using knowledge of language-specific naming conventions. Recognizes when to transliterate a name phonetically vs. translate meaning (e.g., titles). Supports 13 source languages to English, and translation between Chinese, Japanese, and Korean.

compare_addresses

Compare Addresses

Compares two addresses to determine whether they refer to the same location. Accepts both structured addresses (with individual fields) and unstructured addresses (as plain text strings). Can mix structured and unstructured formats.

extract_topics

Extract Topics

Discovers central keywords and concepts from text. Unlike categorization or entity extraction, topic extraction is not constrained by a finite list. It identifies "keyphrases" (exact terms) and "concepts" (broader ideas) ranked by relative importance.

compare_names

Compare Names

Compares two names and returns a similarity score between 0 and 1. Accounts for typographical errors, phonetic spelling variations, transliteration differences, initials, nicknames, and cross-language variations. Supports PERSON, LOCATION, and ORGANIZATION entity types.

deduplicate_names

Deduplicate Names

Identifies and groups duplicate names from a list, accounting for linguistic variations across languages and scripts. Useful for cleaning databases with duplicate records, merging contact lists, or consolidating name data.

split_sentences

Split Sentences

Splits text into individual sentences. Useful for preprocessing text before further NLP analysis, or for breaking large documents into sentence-level units.

categorize_text

Categorize Text

Classifies text content under topic categories drawn from the IAB Quality Assurance Guidelines Taxonomy (Tier 1 contextual categories). Useful for automatically tagging documents, web pages, or articles by topic.

compare_records

Compare Records

Compares structured data records with multiple fields to determine similarity. Each record can contain up to 5 fields of types including name, address, date, number, boolean, and string. Fields can be individually weighted to control their impact on the final match score. Compares left records against right records pairwise.

get_text_embedding

Get Text Embedding

Generates a numerical vector representation (embedding) of text for semantic similarity computation. Transforms text ranging from a single word to an entire document into a vector in semantic space. Supports cross-lingual semantic comparison without translation.

get_syntax_dependencies

Get Syntax Dependencies

Provides syntactic dependency parse trees showing grammatical relationships between tokens in sentences. Each token is annotated with its dependency role (e.g., subject, object, modifier) relative to its head word.

extract_relationships

Extract Relationships

Extracts relationships between entities in text. Identifies the grammatical and semantic connections between two entities, recognizing the action or predicate that connects them. Uses a combination of deep learning and semantic rules.

tokenize_text

Tokenize Text

Splits text into individual tokens (words, numbers, punctuation) using advanced statistical modeling. Particularly useful for languages like Chinese, Japanese, and Thai where word boundaries are not marked by spaces.

extract_entities

Extract Entities

Extracts named entities from text, identifying up to 18 entity types (PERSON, LOCATION, ORGANIZATION, PRODUCT, etc.) across 20 languages. Optionally links entities to Wikidata, DBpedia, or Refinitiv PermID knowledge bases for disambiguation. Can also calculate salience and confidence scores.

list_supported_languages

List Supported Languages

Lists supported language and script combinations or source/target language pairs, including their license status, for a selected Analytics API endpoint. Use this before selecting a language for text analysis or name matching.

get_api_info

Get API Information

Returns the Analytics API service name, version, and build information for the connected cloud or on-premise installation.

Connect Rosette Text Analytics to your AI client

Every client uses the same Magic MCP URL, and so does any other MCP client. Add it once and sign in with SSO.

  1. Enable Rosette Text Analytics in Metorial. In your Metorial portal, enable the Rosette Text Analytics MCP server and sign in with the account that owns the data. Access stays governed by your team policies.
  2. Add a custom connector. Open Customize, then Connectors. Select Add, then Custom, then Web.
  3. Paste your Metorial MCP URL. Name it Metorial, paste your Magic MCP URL (<your-magic-mcp-url>) and continue.
  4. Sign in. Select Add and sign in to load Rosette Text Analytics tools.

Run Rosette Text Analytics through the Metorial gateway

One governed layer for every app your agents reach, not a separate connector per tool.

  • Give Rosette Text Analytics and every other app to your whole team through one MCP gateway, behind your SSO.
  • Scope which teams and agents can use Rosette Text Analytics tools with role-based access control, and trace every call.
  • Prefer to run it yourself? Metorial is open source and self-hostable.

More integrations teams use with Rosette Text Analytics

GitHub

Manage repositories, issues, and pull requests. Create and configure branches, star repositories, review code, and merge changes. Automate CI/CD workflows with GitHub Actions, manage workflow runs, secrets, and artifacts. Track issues with labels, milestones, and assignees. Search across code, repositories, issues, and users. Manage organizations, teams, and memberships. Create and manage projects, gists, packages, deployments, and environments. Access security alerts including code scanning, secret scanning, and Dependabot alerts. Read and write file contents in repositories. Manage webhooks, notifications, and codespaces.

Salesforce

Manage CRM data including Accounts, Contacts, Leads, Opportunities, Cases, and custom objects. Create, read, update, and delete records. Query data using SOQL and search across objects using SOSL. Perform bulk data operations for large-scale imports, exports, and migrations. Execute composite requests to batch multiple operations in a single API call. Access analytics, reports, and dashboards. Manage files and attachments associated with records. Interact with Chatter feeds, posts, and groups for social collaboration. Manage org metadata including custom objects, fields, layouts, and workflows. Query data using GraphQL for precise data retrieval across related objects.

Sharepoint

Manage SharePoint sites, document libraries, lists, and files. Create, read, update, and delete lists and list items with custom columns. Resolve site users to numeric Person/Group LookupId values. Upload, download, move, copy, and version files in document libraries. Search across sites, files, folders, lists, and list items using Microsoft Search. Manage permissions at site, list, and item levels with granular access control. Define and manage content types and site columns. Retrieve site properties and search for sites across Microsoft 365.

Airtable

Create, read, update, and delete records in Airtable bases and tables. Manage base schemas including creating tables and fields. Filter records using formulas, sort by fields, and scope queries to specific views. Upsert records to find, create, or update in a single call. Upload attachments to records, read and write record comments, list accessible bases, and receive real-time base change events through webhooks.

Sentry

Track, manage, and resolve application errors and performance issues. List, query, and bulk-update issues and error events with filters like status, assignment, and tags. Create and manage releases, associate commits, and upload source maps. Configure issue alert rules and metric alert rules with notification actions. Set up cron monitors to detect missed or failed scheduled jobs. Build custom dashboards with configurable widgets. Run ad-hoc Discover queries across errors and transactions for performance analysis. Manage organizations, teams, projects, and members. Provision users via SCIM. Access session replay data.

Bitbucket

Manage Git repositories, pull requests, and CI/CD pipelines on Bitbucket Cloud. Create, fork, and configure repositories within workspaces and projects. Create, review, approve, merge, and decline pull requests with inline code comments. Browse source code, list commits, and manage branches and tags. Trigger, monitor, and manage Bitbucket Pipelines. List workspace members, configure repository default reviewers and branch restrictions, create and manage repository webhooks, and search code across repositories.

Technical notes for Rosette Text Analytics

Analyze unstructured and semi-structured text using natural language processing across Asian, European, and Middle Eastern languages. Extract entities (persons, locations, organizations, products) and link them to knowledge bases like Wikidata and DBpedia. Determine sentiment at document or entity level. Compare and match names across languages accounting for transliterations, nicknames, and spelling variations. Translate names between 13+ languages. Deduplicate name lists across scripts. Compare address and record similarity. Extract relationships and events connecting entities. Categorize documents by topic using IAB taxonomy. Discover keyphrases and concepts via topic extraction. Perform morphological analysis including part-of-speech tagging, lemmatization, and compound decomposition. Tokenize text, detect sentences, identify languages (55 supported), compute semantic similarity via text embeddings, parse syntactic dependencies, and transliterate text between scripts.

Frequently asked questions

Common questions about connecting Rosette Text Analytics to AI agents with Metorial.

  1. How many tools does the Rosette Text Analytics MCP server have?
    The Rosette Text Analytics MCP server exposes 19 tools, including Transliterate Text, Analyze Sentiment, Analyze Morphology. Each one is governed and traced through Metorial.
  2. Rosette Text Analytics exposes tools your agents call on demand; it does not publish event triggers yet. Everything still runs through one governed MCP URL.
  3. Any MCP client, including VS Code, Windsurf, Zed, OpenCode and Grok. Each one reaches the Rosette Text Analytics MCP server through the same Metorial URL.
  4. Use role-based access control to decide which teams, users, and agents can use Rosette Text Analytics and which of its tools they can call.
  5. Yes. Metorial is open source, so you can run the Rosette Text Analytics MCP server yourself or use the hosted gateway.

Connect Rosette Text Analytics to production AI agents

See how Metorial gives your team governed access to Rosette Text Analytics, with tracing and security controls built in.