$ loading_
Safely download, extract, and compare tender documents with structured text signals.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "tender-documents-mcp" yet — see the docs or source repo.
Please download this public tender ZIP archive, extract the PDF and Office files inside, pull the full text, and return structured signals such as file type, page count, or parsing status.
A list of extracted files, the parsed text from each document, and related structured extraction metadata.
Please compare these two tender documents, extract their text, and summarize the key differences, especially changes in eligibility requirements, technical specifications, and submission deadlines.
A comparison summary highlighting document differences, organized by key changed sections.
I have Base64 data for a tender document. Please decode it, extract the document text, and report the file type and processing result.
The decoded document type, extracted text content, and a status report of the processing.
Researchers or office workers can use it to safely download public tender materials in PDF, Office, and ZIP formats and convert them into searchable text. This reduces the manual effort of opening and copying content.
When multiple versions of the same tender are released, users can extract the text and compare documents to quickly locate changed clauses. This is useful for tracking updates to eligibility rules, technical requirements, or deadlines.
If documents are passed from other systems as Base64 data, this tool can directly extract and parse the content. Users do not need to manually restore the file before processing it.
Based on the description, it can safely download and extract public tender documents from PDFs, Office files, and ZIP archives, then output text and structured signals.
Yes. The description explicitly says it supports document comparison, which can be used to compare different tender documents or different versions.
The provided information does not specify installation steps, runtime requirements, or API keys. For details, see the source repository.
Extract text, images, and tables from PDFs with multilingual analysis.
Efficiently extracts structured data from complex documents and Excel with lower token usage.
Extract text and metadata from PDFs via URL or Base64 input.
Extract structured data from academic PDFs with natural-language querying and batch workflows.
Read, create, and manage documents with OCR, styling, and categorization.
Read and stream office documents as Markdown for analysis and processing.