{"$schema":"https://wellknown.network/schemas/agent-record-v1.json","schemaVersion":"1","id":"ag_bbc98e6ztyky","handle":"mcp-polaris-ai-datainsight","url":"https://wellknown.network/agents/mcp-polaris-ai-datainsight","links":{"self":"https://wellknown.network/agents/mcp-polaris-ai-datainsight/record.json","html":"https://wellknown.network/agents/mcp-polaris-ai-datainsight","markdown":"https://wellknown.network/agents/mcp-polaris-ai-datainsight/record.md","api":"https://wellknown.network/api/v1/agents/mcp-polaris-ai-datainsight","status":"https://wellknown.network/api/v1/agents/mcp-polaris-ai-datainsight/status","claim":"https://wellknown.network/agents/mcp-polaris-ai-datainsight/claim","claimApi":"https://wellknown.network/api/v1/claims","claimDescriptor":"https://wellknown.network/agents/mcp-polaris-ai-datainsight/claim.json","badge":"https://wellknown.network/agents/mcp-polaris-ai-datainsight/badge.svg","openapi":"https://wellknown.network/openapi.json","history":"https://wellknown.network/api/v1/agents/mcp-polaris-ai-datainsight/history","tools":"https://wellknown.network/api/v1/agents/mcp-polaris-ai-datainsight/tools"},"ard":{"identifier":"urn:air::server:mcp-polaris-ai-datainsight","type":"application/mcp-server-card+json"},"kind":"mcp_server","declared":{"name":"mcp-polaris-ai-datainsight","summary":"This tool supports the extraction of text, images, and other elements from various document formats.","description":"# mcp-polaris-ai-datainsight\n\n[Polaris AI DataInsight](https://datainsight.polarisoffice.com/) is an API service that easily converts documents in various formats into structured data (such as JSON).\n\nThis tool supports the extraction of text, images, and other elements from various document formats (e.g. .docx, .pptx, .xlsx, .hwp, .hwpx).\n\nFor more details, please refer to the [documentation](https://datainsight.polarisoffice.com/documentation/overview).\n\n## Features\n\n### 1. Extract content from document\nExtract text, images, and other elements from various document formats.\n- Supported document formats : docx, xlsx, pptx, hwpx, hwp\n- Supported elements types : text, table, image, chart, shape, header, footer, caption\n- Images in the document are stored on local storage, and the corresponding image paths are included in the JSON output.\n- Tables are represented in JSON format, as illustrated in [this example](examples/example_tool_output.json).\n\n### 2. List files in allowed directories\nList the files in the directory path set in the `POLARIS_AI_DATA_INSIGHT_RESOURCES_DIR` environment variable (in the case of Docker, the path mounted to `/app/readable`).\n- Used to retrieve file paths to be passed as arguments to the \"Extract content from document\" Tool.\n\n## Installation and Setup\n\n### Prerequisites\n\nTo use this server, follow these steps:\n1. Generate an API key.\n    - Refer to [this guide](https://datainsight.polarisoffice.com/documentation/quickstart) to generate an API key.\n\n2. [Install `uv`](https://docs.astral.sh/uv/getting-started/installation/).\n3. Create a **writable** directory for storing extraction-result resources(e.g. images in files), and set its path in the `POLARIS_AI_DATA_INSIGHT_RESOURCES_DIR` environment variable. \n\nAfter that, choose one of the installation methods below and start the server.\n\n### Method 1: Manual Configuration\n\nIf you prefer a manual setup, add the following configuration to your IDE's MCP config file:\n\n```json\n{\n  \"mcpServers\":…","publisher":{"name":"Polaris Office","url":null},"homepage":"https://datainsight.polarisoffice.com/","repository":"https://github.com/PolarisOfficeRnD/PolarisAIDataInsight/","version":"1.0.0","license":null,"protocols":["mcp"],"tags":["polaris","datainsight","mcp"],"pricing":null,"endpoints":[{"url":"pypi:mcp-polaris-ai-datainsight","type":"package_pypi","auth":null,"probeable":false}],"skills":null,"tools":null,"extra":null,"attribution":{"kind":"pypi","name":"pypi","repoUrl":"pypi","summary":"pypi","version":"pypi","description":"pypi","homepageUrl":"pypi","publisherName":"pypi"}},"derived":{"capabilities":[{"slug":"documents.extraction","name":"Data Extraction","confidence":0.894,"provenance":"derived"},{"slug":"dev.filesystem","name":"Filesystem","confidence":0.802,"provenance":"derived"},{"slug":"documents.conversion","name":"Document Conversion","confidence":0.768,"provenance":"derived"}],"categories":["dev","documents"],"language":"en"},"observed":{"status":"unknown","statusReason":"Distributed as a package to run locally; no network endpoint to check.","lastOkAt":null,"lastProbedAt":null,"statusComputedAt":null,"reliability30d":null,"latestObservations":[],"tools":null,"package":{"name":"mcp-polaris-ai-datainsight","registry":"pypi","observedAt":"2026-10-28T12:23:02.943Z","publishedAt":"2025-09-17T09:17:34.320582Z","latestVersion":"1.0.0"},"toolSurface":null,"endpointFacts":[]},"verification":{"claimed":false,"claimedAt":null,"proofs":[]},"provenance":{"sources":[{"source":"pypi","key":"mcp-polaris-ai-datainsight","url":"https://pypi.org/project/mcp-polaris-ai-datainsight/","firstSeenAt":"2026-09-10T03:18:41.283Z","fetchedAt":"2026-10-28T12:22:02.411Z","normalizedAt":"2026-10-28T12:22:02.411Z"}]},"firstSeenAt":"2026-09-10T03:18:41.283Z","updatedAt":"2026-10-28T12:23:02.943Z"}