{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"github_mcp-haris-musa-excel-mcp-server","slug":"mcp-haris-musa-excel-mcp-server","name":"excel-mcp-server","type":"mcp","url":"https://github.com/haris-musa/excel-mcp-server","page_url":"https://unfragile.ai/mcp-haris-musa-excel-mcp-server","categories":["mcp-servers"],"tags":["ai","automation","excel","llm","mcp","mcp-server","sse","stdio","streamable-http","toolcalling"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"github_mcp-haris-musa-excel-mcp-server__cap_0","uri":"capability://tool.use.integration.multi.transport.mcp.server.with.stdio.http.sse.and.streamable.protocols","name":"multi-transport mcp server with stdio, http/sse, and streamable protocols","description":"Implements a Model Context Protocol server using FastMCP framework that bridges three distinct transport mechanisms (stdio for local IDE integration, HTTP with Server-Sent Events for remote services, and streamable HTTP for streaming responses) to the same underlying Excel operation logic. The server uses typer CLI to provide mode selection at startup, abstracting transport complexity from tool implementations while maintaining protocol-agnostic tool definitions via @mcp.tool() decorators.","intents":["I need to expose Excel operations to Claude Desktop, Cursor IDE, and remote AI services through a single server implementation","I want to support both local development (stdio) and cloud deployment (HTTP/SSE) without duplicating tool logic","I need to stream large Excel operation results back to clients without blocking the connection"],"best_for":["AI agent developers building multi-client integrations","teams deploying MCP servers to both local IDEs and cloud platforms","builders needing protocol abstraction for tool-calling systems"],"limitations":["SSE transport limited to port 8017 by default — requires custom configuration for multi-instance deployments","Stdio transport provides no built-in authentication — relies on client-side access control","HTTP/SSE modes require EXCEL_FILES_PATH environment variable — no fallback to current working directory"],"requires":["Python 3.9+","FastMCP framework (included in pyproject.toml)","typer CLI library for mode selection"],"input_types":["JSON-RPC requests (MCP protocol format)","tool parameters as JSON objects"],"output_types":["JSON-RPC responses","Server-Sent Events (SSE) streams for HTTP mode","stdout/stderr for stdio mode"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-haris-musa-excel-mcp-server__cap_1","uri":"capability://data.processing.analysis.openpyxl.backed.workbook.creation.and.metadata.retrieval","name":"openpyxl-backed workbook creation and metadata retrieval","description":"Provides programmatic workbook creation and metadata extraction using the openpyxl library, which operates without requiring Microsoft Excel installation. The implementation wraps openpyxl's Workbook class to create new Excel files with configurable properties (title, author, subject, keywords) and retrieves workbook-level metadata including sheet names, dimensions, and document properties through openpyxl's metadata API.","intents":["I need to create new Excel workbooks from AI agent instructions without Excel being installed","I want to read workbook metadata (sheet count, dimensions, properties) to understand file structure before processing","I need to set document properties (author, title, subject) programmatically for compliance or tracking"],"best_for":["developers building headless Excel automation","teams running Excel operations in containerized/serverless environments","AI agents that need to inspect workbook structure before data operations"],"limitations":["openpyxl does not support .xls (legacy Excel 97-2003) format — only .xlsx and .xlsm","Metadata retrieval does not include VBA macro information or external data connections","Creating workbooks with complex templates or custom XML parts requires manual openpyxl manipulation outside this tool"],"requires":["Python 3.9+","openpyxl library (included in dependencies)","write permissions to target file path"],"input_types":["file path (string)","workbook properties (title, author, subject, keywords as optional strings)"],"output_types":["workbook object (openpyxl.Workbook)","metadata dictionary (sheet names, dimensions, properties)"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-haris-musa-excel-mcp-server__cap_10","uri":"capability://safety.moderation.error.handling.and.response.formatting.with.mcp.compliant.error.codes","name":"error handling and response formatting with mcp-compliant error codes","description":"Implements comprehensive error handling that catches openpyxl exceptions, file I/O errors, and validation failures, then formats them as MCP-compliant error responses with structured error codes and human-readable messages. The server uses try-except blocks in each tool to catch specific exceptions (FileNotFoundError, ValueError, openpyxl.utils.exceptions.InvalidFileException) and maps them to MCP error codes (e.g., -32600 for invalid request, -32603 for internal error). Error responses include context information (file path, operation, root cause) to aid debugging without exposing sensitive system details.","intents":["I need to understand why an Excel operation failed (file not found, invalid formula, permission denied)","I want error responses in MCP format so my client can handle them programmatically","I need to debug tool failures without exposing internal server state or file paths"],"best_for":["AI agent developers building robust error handling","teams integrating MCP servers with error monitoring/logging","developers debugging tool failures in production"],"limitations":["Error messages are generic to avoid information disclosure — specific openpyxl exception details are logged but not returned to client","Stack traces are not included in error responses — full debugging requires server-side log access","File permission errors are not distinguished from file not found — both return similar error messages","Timeout errors are not handled — long-running operations may hang without error response"],"requires":["Python 3.9+","MCP protocol implementation (FastMCP)","exception handling in each tool function"],"input_types":["any tool input that triggers an error condition"],"output_types":["MCP error response (JSON object with code, message, data fields)"],"categories":["safety-moderation","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-haris-musa-excel-mcp-server__cap_11","uri":"capability://automation.workflow.concurrent.workbook.access.with.in.memory.state.management","name":"concurrent workbook access with in-memory state management","description":"Manages multiple concurrent Excel workbook operations through openpyxl's in-memory workbook model, where each tool call loads a workbook into memory, performs operations, and saves changes back to disk. The server does not maintain persistent workbook state between requests — each request is stateless and independent. This approach avoids file locking issues that plague Excel COM automation but requires explicit save operations after modifications. The implementation uses openpyxl's load_workbook() and save() methods with optional data_only parameter to control formula evaluation.","intents":["I need to perform multiple Excel operations concurrently without file locking conflicts","I want to avoid Excel COM overhead and process multiple workbooks in parallel","I need stateless tool execution where each request is independent and can be retried"],"best_for":["AI agents performing parallel Excel operations","teams running multiple MCP server instances with shared file storage","developers building scalable Excel automation services"],"limitations":["No transaction support — partial failures leave workbooks in inconsistent state (e.g., data written but formatting not applied)","Concurrent writes to the same file may cause data loss — last write wins without conflict detection","Large workbooks (>100MB) consume significant memory — no streaming or lazy-loading support","Workbook state is not shared between requests — each request reloads the file from disk, adding latency","No optimistic locking or version control — concurrent modifications are not detected"],"requires":["Python 3.9+","openpyxl library","sufficient memory for largest workbook size","file system with atomic write support (for save operations)"],"input_types":["file path (string)","tool-specific parameters"],"output_types":["tool-specific results","confirmation of save operation"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-haris-musa-excel-mcp-server__cap_2","uri":"capability://data.processing.analysis.intelligent.data.read.write.with.header.detection.and.type.inference","name":"intelligent data read/write with header detection and type inference","description":"Implements bidirectional data operations that automatically detect Excel headers, infer data types, and handle sparse data ranges. The read operation scans the first row to identify headers, then extracts data with type preservation (dates, numbers, strings). The write operation accepts structured data (list of dicts or 2D arrays) and intelligently maps columns to existing headers or creates new ones, with optional header row insertion and cell-level type coercion through openpyxl's cell value assignment.","intents":["I want to read Excel data into a structured format (JSON/dict) without manually specifying column ranges","I need to write data from Python objects (dicts, DataFrames) directly to Excel with automatic header mapping","I need to preserve data types (dates, numbers, booleans) when reading/writing, not convert everything to strings"],"best_for":["AI agents performing data extraction and transformation workflows","developers building ETL pipelines that treat Excel as a data source/sink","teams migrating between Excel and structured data formats (JSON, CSV, databases)"],"limitations":["Header detection only scans the first row — multi-row headers or merged header cells are not supported","Type inference is heuristic-based (regex for dates, numeric parsing) — ambiguous values default to string type","Sparse data (non-contiguous ranges) are read as continuous blocks — gaps are filled with None/null","Write operation does not support cell-level formatting preservation from source data — only values are transferred"],"requires":["Python 3.9+","openpyxl library","valid Excel file path (for read) or writable path (for write)","data in list-of-dicts or 2D array format for write operations"],"input_types":["file path (string)","sheet name (string, defaults to active sheet)","data range (optional, defaults to used range)","structured data: list of dicts or 2D array for write"],"output_types":["list of dicts (read operation, one dict per row with headers as keys)","None (write operation, modifies file in-place)"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-haris-musa-excel-mcp-server__cap_3","uri":"capability://automation.workflow.worksheet.lifecycle.management.create.copy.delete.rename","name":"worksheet lifecycle management (create, copy, delete, rename)","description":"Provides CRUD operations for Excel worksheets through openpyxl's worksheet API. Creation adds new sheets with optional positioning and default properties. Copy duplicates an entire sheet including formulas, formatting, and data while optionally renaming. Delete removes sheets with validation to prevent removing the last sheet. Rename updates sheet names with collision detection. All operations maintain workbook integrity and update internal sheet references.","intents":["I need to create multiple worksheets programmatically for organizing different data categories","I want to duplicate a sheet template and rename it for batch processing","I need to remove obsolete sheets and reorganize workbook structure"],"best_for":["AI agents building multi-sheet workbooks from structured data","developers automating workbook reorganization tasks","teams using sheets as logical data partitions in larger workflows"],"limitations":["Copy operation does not preserve sheet-level protection or hidden state — only data and formatting","Delete operation prevents removal of the last sheet in a workbook — at least one sheet must remain","Rename operation does not update formula references across sheets — external sheet references must be manually updated","Sheet positioning (insert_after parameter) is relative to existing sheets — no absolute positioning API"],"requires":["Python 3.9+","openpyxl library","valid workbook object loaded in memory","write permissions to save changes"],"input_types":["sheet name (string)","optional: new sheet name (for rename)","optional: position/insert_after parameter (for create)","optional: source sheet name (for copy)"],"output_types":["worksheet object (openpyxl.worksheet.worksheet.Worksheet)","confirmation message (string)"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-haris-musa-excel-mcp-server__cap_4","uri":"capability://automation.workflow.range.based.cell.formatting.with.styles.fonts.colors.borders.and.merging","name":"range-based cell formatting with styles, fonts, colors, borders, and merging","description":"Applies visual formatting to cell ranges using openpyxl's Style, Font, PatternFill, Border, and Alignment objects. The format_range operation accepts a range specification (e.g., 'A1:C10') and applies multiple style attributes (font color, background color, bold, italic, borders, alignment) in a single operation. Merge and unmerge operations combine or split cells while preserving content in the top-left cell. All formatting is applied directly to the openpyxl cell objects without requiring Excel to be running.","intents":["I need to apply consistent styling (colors, fonts, borders) to data ranges for readability","I want to merge cells for headers or labels while maintaining data integrity","I need to create visually distinct sections in a worksheet (e.g., title area, data area, summary area)"],"best_for":["AI agents generating formatted reports from data","developers building Excel templates programmatically","teams automating workbook styling for brand consistency"],"limitations":["Formatting does not support conditional formatting rules — only static cell-level styles","Merge operation only preserves content from top-left cell — data in other merged cells is discarded","Border styling is applied per-cell, not per-range — complex border patterns require cell-by-cell specification","Font size and color are limited to openpyxl's supported values — some Excel-specific fonts may not render identically"],"requires":["Python 3.9+","openpyxl library with Style, Font, PatternFill, Border support","valid range specification (e.g., 'A1:C10' or cell coordinates)","workbook object in memory"],"input_types":["range specification (string, e.g., 'A1:C10')","style parameters: font_color, bg_color, bold, italic, border_style, alignment (all optional)"],"output_types":["confirmation message (string)","modified worksheet object"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-haris-musa-excel-mcp-server__cap_5","uri":"capability://data.processing.analysis.formula.application.and.syntax.validation","name":"formula application and syntax validation","description":"Enables programmatic formula insertion and validation using openpyxl's formula handling. The apply_formula operation accepts a cell reference and formula string (e.g., '=SUM(A1:A10)'), assigns it to the cell, and optionally calculates the result if data_only mode is enabled. The validate_formula_syntax operation parses formula strings to detect syntax errors (unmatched parentheses, invalid function names, circular references) without executing the formula, using regex-based validation and openpyxl's formula parser.","intents":["I need to insert calculated columns (SUM, AVERAGE, VLOOKUP) into Excel data programmatically","I want to validate formula syntax before writing to Excel to catch errors early","I need to create dynamic formulas that reference other cells or sheets"],"best_for":["AI agents generating Excel reports with calculated fields","developers automating formula-heavy workbooks (financial models, dashboards)","teams validating user-provided formulas before insertion"],"limitations":["Formula validation is syntax-only — does not check if referenced cells/ranges exist or have compatible data types","Circular reference detection is basic — complex circular patterns may not be caught","Formula calculation requires data_only=True mode, which disables formula editing in Excel — read-only after calculation","Advanced Excel functions (array formulas, dynamic arrays) may not be fully supported by openpyxl's parser","Cross-sheet formula references require exact sheet name matching — no fuzzy matching or alias resolution"],"requires":["Python 3.9+","openpyxl library with formula support","valid cell reference (e.g., 'A1', 'Sheet2!B5')","formula string in Excel syntax (e.g., '=SUM(A1:A10)')"],"input_types":["cell reference (string, e.g., 'A1' or 'Sheet2!B5')","formula string (string, must start with '=')","optional: data_only flag (boolean, for calculation)"],"output_types":["calculated value (if data_only=True)","formula string (if data_only=False)","validation result (boolean or error message)"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-haris-musa-excel-mcp-server__cap_6","uri":"capability://automation.workflow.chart.creation.with.multiple.types.line.bar.pie.scatter.and.data.binding","name":"chart creation with multiple types (line, bar, pie, scatter) and data binding","description":"Generates Excel charts programmatically using openpyxl's Chart classes (LineChart, BarChart, PieChart, ScatterChart, etc.). The create_chart operation accepts a chart type, data range, optional categories/series configuration, and chart properties (title, axis labels). Charts are bound to worksheet data ranges through openpyxl's add_data() and set_categories() methods, which establish dynamic links to source cells. Charts are then embedded in the worksheet at a specified anchor cell.","intents":["I need to generate charts from Excel data without opening Excel or using VBA","I want to create dashboard-style workbooks with multiple chart types visualizing the same data","I need to automate chart creation for reports that are regenerated with new data"],"best_for":["AI agents generating data visualization reports","developers building automated dashboard workbooks","teams creating templated Excel reports with dynamic charts"],"limitations":["Chart styling options are limited to openpyxl's Chart class properties — advanced formatting (gradients, custom shapes) requires manual Excel editing","Data binding is range-based — charts do not automatically update if source data is added/removed (static range references)","3D charts and some advanced chart types (waterfall, funnel) are not supported by openpyxl","Chart positioning is anchor-cell based — precise pixel-level positioning is not available","Legend and axis label customization is basic — complex label formatting requires post-creation Excel editing"],"requires":["Python 3.9+","openpyxl library with Chart classes","valid data range (e.g., 'A1:C10') with numeric data","worksheet object with data already populated"],"input_types":["chart type (string: 'line', 'bar', 'pie', 'scatter', 'area', 'column')","data range (string, e.g., 'A1:C10')","optional: categories range (string, for X-axis labels)","optional: chart title, axis labels (strings)","optional: anchor cell (string, e.g., 'E2' for chart position)"],"output_types":["chart object (openpyxl.chart.Chart subclass)","confirmation message with chart type and position"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-haris-musa-excel-mcp-server__cap_7","uri":"capability://data.processing.analysis.pivot.table.creation.with.configurable.row.column.value.fields","name":"pivot table creation with configurable row/column/value fields","description":"Generates Excel pivot tables programmatically using openpyxl's PivotTable class. The create_pivot_table operation accepts a source data range, field specifications (row fields, column fields, value fields with aggregation functions like SUM, COUNT, AVERAGE), and optional filtering/sorting. Pivot tables are created in a separate worksheet and linked to the source data through openpyxl's pivot table API, which generates the underlying XML structure without requiring Excel to be running.","intents":["I need to create pivot tables from raw data for aggregation and analysis without Excel","I want to generate multi-dimensional summaries (e.g., sales by region and product) programmatically","I need to automate pivot table creation for recurring reports with changing source data"],"best_for":["AI agents performing data aggregation and summarization","developers building analytical workbooks with pivot table summaries","teams automating business intelligence report generation"],"limitations":["Pivot table styling and formatting options are minimal — openpyxl does not expose Excel's pivot table design templates","Calculated fields and custom aggregations are not supported — only built-in functions (SUM, COUNT, AVERAGE, MIN, MAX)","Pivot table refresh is manual in Excel — openpyxl does not provide programmatic refresh capability","Slicers and timeline controls are not supported by openpyxl","Pivot table placement is worksheet-based — cannot create multiple pivot tables in the same worksheet"],"requires":["Python 3.9+","openpyxl library with PivotTable support","valid source data range (e.g., 'Data!A1:D100') with headers","field specifications: row_fields, column_fields, value_fields (lists of field names)"],"input_types":["source data range (string, e.g., 'Data!A1:D100')","row fields (list of strings, e.g., ['Region', 'Product'])","column fields (list of strings, optional)","value fields (list of dicts with field name and aggregation function, e.g., [{'field': 'Sales', 'function': 'sum'}])","optional: target worksheet name (string, defaults to 'PivotTable')"],"output_types":["pivot table object (openpyxl.worksheet.pivot_table.PivotTable)","confirmation message with field configuration"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-haris-musa-excel-mcp-server__cap_8","uri":"capability://automation.workflow.native.excel.table.creation.with.automatic.filtering.and.styling","name":"native excel table creation with automatic filtering and styling","description":"Creates native Excel tables (ListObjects in Excel terminology) using openpyxl's Table class, which enables built-in filtering, sorting, and structured references. The create_table operation accepts a data range, optional table name, and style template. Tables are created with automatic header row detection and built-in filter buttons on each column header. The implementation uses openpyxl's Table and TableStyleInfo classes to apply predefined Excel table styles (Light1, Medium2, Dark3, etc.) without manual cell-by-cell formatting.","intents":["I need to create Excel tables with automatic filtering for end-user data exploration","I want to apply consistent table styling (alternating row colors, header formatting) programmatically","I need to enable structured references (table[column_name]) for formulas in related cells"],"best_for":["AI agents generating user-facing Excel reports with interactive tables","developers creating data entry templates with built-in filtering","teams automating table creation for data distribution workbooks"],"limitations":["Table styles are limited to Excel's built-in templates — custom color schemes require post-creation Excel editing","Structured references (table[column]) work in Excel but may not be fully supported by openpyxl's formula parser","Table expansion (adding rows) is manual in Excel — openpyxl does not provide programmatic row insertion into tables","Slicers and timeline controls cannot be attached to tables through openpyxl","Table names must be unique within the workbook — no automatic name collision handling"],"requires":["Python 3.9+","openpyxl library with Table and TableStyleInfo support","valid data range (e.g., 'A1:D10') with headers in the first row","worksheet object with data already populated"],"input_types":["data range (string, e.g., 'A1:D10')","optional: table name (string, defaults to 'Table1', 'Table2', etc.)","optional: style template (string, e.g., 'Light1', 'Medium2', 'Dark3')"],"output_types":["table object (openpyxl.worksheet.table.Table)","confirmation message with table name and range"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-haris-musa-excel-mcp-server__cap_9","uri":"capability://automation.workflow.environment.aware.file.path.resolution.with.transport.specific.handling","name":"environment-aware file path resolution with transport-specific handling","description":"Implements transport-specific file path resolution logic that adapts to the deployment context. For stdio transport (local IDE integration), file paths are provided by the client with each tool call, enabling flexible per-request path specification. For HTTP/SSE transports (remote deployment), the server reads the EXCEL_FILES_PATH environment variable to establish a root directory, and all file operations are scoped to this root with path traversal protection. The implementation uses os.path.join() and path normalization to prevent directory escape attacks while maintaining cross-platform compatibility.","intents":["I need to deploy the MCP server to both local IDEs (Cursor) and cloud platforms with different path handling","I want to restrict file operations to a specific directory in remote deployments for security","I need to support both absolute paths (local) and relative paths (remote) without code duplication"],"best_for":["DevOps teams deploying MCP servers to multiple environments","developers building multi-tenant Excel automation services","teams requiring path isolation for security and resource management"],"limitations":["EXCEL_FILES_PATH environment variable is required for HTTP/SSE modes — no fallback to current working directory","Path traversal protection uses simple normalization — symlink attacks are not prevented","Absolute paths are rejected in HTTP/SSE modes — all paths must be relative to EXCEL_FILES_PATH","Windows and Unix path separators are handled by os.path.join() — cross-platform consistency depends on correct environment setup"],"requires":["Python 3.9+","EXCEL_FILES_PATH environment variable (for HTTP/SSE modes)","read/write permissions to target directory"],"input_types":["file path (string, format depends on transport: absolute for stdio, relative for HTTP/SSE)"],"output_types":["resolved file path (string, normalized and validated)"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":46,"verified":false,"data_access_risk":"high","permissions":["Python 3.9+","FastMCP framework (included in pyproject.toml)","typer CLI library for mode selection","openpyxl library (included in dependencies)","write permissions to target file path","MCP protocol implementation (FastMCP)","exception handling in each tool function","openpyxl library","sufficient memory for largest workbook size","file system with atomic write support (for save operations)"],"failure_modes":["SSE transport limited to port 8017 by default — requires custom configuration for multi-instance deployments","Stdio transport provides no built-in authentication — relies on client-side access control","HTTP/SSE modes require EXCEL_FILES_PATH environment variable — no fallback to current working directory","openpyxl does not support .xls (legacy Excel 97-2003) format — only .xlsx and .xlsm","Metadata retrieval does not include VBA macro information or external data connections","Creating workbooks with complex templates or custom XML parts requires manual openpyxl manipulation outside this tool","Error messages are generic to avoid information disclosure — specific openpyxl exception details are logged but not returned to client","Stack traces are not included in error responses — full debugging requires server-side log access","File permission errors are not distinguished from file not found — both return similar error messages","Timeout errors are not handled — long-running operations may hang without error response","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.5632647095403794,"quality":0.34,"ecosystem":0.6000000000000001,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:22.065Z","last_scraped_at":"2026-05-03T14:23:34.856Z","last_commit":"2026-04-12T06:14:45Z"},"community":{"stars":3780,"forks":413,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=mcp-haris-musa-excel-mcp-server","compare_url":"https://unfragile.ai/compare?artifact=mcp-haris-musa-excel-mcp-server"}},"signature":"4OI+NWjb4CbpwoepsKFwNJsiJ/2j8EJOTJmcEcBYqVqZbxnd6ZQJxOvreYZkMGTwty72uM29BfeeaJBgnjnPCw==","signedAt":"2026-06-21T13:01:42.829Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/mcp-haris-musa-excel-mcp-server","artifact":"https://unfragile.ai/mcp-haris-musa-excel-mcp-server","verify":"https://unfragile.ai/api/v1/verify?slug=mcp-haris-musa-excel-mcp-server","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}