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tiny-context — efficient file tools by AVRG3

Local document queries, saved extraction profiles, spreadsheet SQL, logs and keyed JSON changes.

Connector by Warddamn · GitHub account verified by the MCP Registry

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Local document queries, saved extraction profiles, spreadsheet SQL, logs and keyed JSON changes.

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Permissions

What this server can do and what it asks for, from its tool list and install config. Checked Oct 25, 2026.

Tools
6 read · 0 write · 0 delete · 2 not yet classified
Secrets
None asked for
Install scripts
Not scanned yet
Runs as
Downloaded binary

Tools by what they do 8

Read from the source code; the running server may list different tools.

Read 6 · Look things up without changing anything.

  • diff_files
  • extract
  • query_file
  • read_section
  • summarize_log
  • validate_file

Not yet classified 2 · We could not tell from the name and description.

  • file_map
  • query_table

Network hosts it talks to 1

  • github.com · found in install command

Files it touches

  • Any path the agent passes to its tools

Tools (8)

Read from the source code; the running server may differ. Descriptions are the server’s own words; hidden characters are shown as [U+…].

  • diff_filesCompare documents or keyed JSON records

    Compare two files and report what changed — works outside git and on PDF/DOCX/PPTX/XLSX/CSV (tables get added/removed/changed row counts + samples; documents diff on extracted text). USE WHEN: "what changed between v1 and v2", "compare these spreadsheets", or "which orders/issues/inventory records changed between two API exports despite shuffled rows" (records mode, explicit key). PREFER OVER: reading both files and comparing in your head; git diff when the files aren't in git or aren't plain text. git diff is fine for tracked plain-text files. DOES NOT: fetch snapshots, infer IDs, remember pr…

  • extractPull matches/values out of files

    Extract values with locations: regex, jq, built-in kinds, or reusable document profiles. USE WHEN: emails/URLs/IDs; batch recurring labeled forms using a saved profile (up to 100 txt/md/docx/text-layer PDFs). PREFER OVER: repeated reads/field calls. Read/Grep for one small text file; reuse an existing correct script. DOES NOT: train, infer templates, OCR, verify meaning or guarantee cost savings. Profiles recheck exact anchors/unique labels; mismatches need review. Save rules once with Write/editor; docs/DOCUMENT_PROFILES.md. EXAMPLE: extract({paths:["/abs/*.docx"],profile:"/abs/profile.json",…

  • file_mapOutline a file or directory without reading it

    Structural outline of a file or directory WITHOUT its contents: headings (md/docx), function/class signatures (code), sheets + column headers + row counts (xlsx), slide titles (pptx), page count + outline + first line per page (pdf), size-annotated tree (directory). USE WHEN: "what's in this file/folder", "outline this document", "which functions are in here", "what sheets and columns does this spreadsheet have", or before deciding what to read. PREFER OVER: reading an entire large document just to learn its structure, or ls+grep+head loops for directories. If the question or section is alread…

  • query_fileFind ranked passages in documents

    Ranked passages matching a query inside one or many files (txt/md/code/pdf/docx/pptx/xlsx/csv), each with its exact location, so the follow-up read is surgical. USE WHEN: "where does the contract discuss termination", "does this deck mention pricing", "find every place the spec talks about retries", "which of these docs cover X". PREFER OVER: Read/cat of a LARGE file (> ~20 KB) just to find one passage; Grep for PDFs/DOCX/PPTX/XLSX (Grep can't open them) and for ranking across many files. Read is fine — and sufficient — for a small plain-text file: if you have already Read a file, you have eve…

  • query_tableQuery a CSV/XLSX/Parquet with SQL

    Run SQL (DuckDB) over a CSV/TSV/Parquet/XLSX file without the data ever entering your context. The file is table `t`. USE WHEN: "total sales by region", "how many rows have a negative total", "top 10 customers", "which columns exist and what types", any aggregate/filter/join-free question about a table. PREFER OVER: Read/cat/head of the table, writing a pandas/awk script, or loading rows to count them. Read is fine for a tiny table (< ~50 rows) you need verbatim. LIMITS: one read-only SELECT or DESCRIBE; no SQL file/network access, COPY, extensions, or multiple statements. Input/export cap 64 …

  • read_sectionRead one located section of a file

    The surgical read: returns ONLY the located section of a file — a heading's section, a page range, a line range, DOCX paragraphs, an XLSX sheet range, or PPTX slides — capped at max_tokens. USE WHEN: you know where the content is (from the task, file_map or query_file) and need the actual text of just that part; reading pages of a PDF, a sheet of a workbook, a section of a long doc. PREFER OVER: Read/cat of the whole file when you need a slice, and always for PDF/DOCX/XLSX/PPTX (Read can't slice them). Read is fine for small plain-text files you need in full. DOES NOT: search (use query_file),…

  • summarize_logCluster and time-bucket a log file

    Structure of a log file in ~300 tokens: repeated-message clusters (numbers/ids/paths masked) with counts, first/last time and one sample each, level counts, and a rate timeline — from 80k lines without reading them. USE WHEN: "what's causing the 5xx spike", "summarize this log", "what errors are in here", "when did the failures start", before grepping. PREFER OVER: tail/head/grep loops and Read on any log over a few hundred lines; run this first, then Grep/extract for the specific message. Read is fine for a log under ~100 lines. DOES NOT: follow files live, parse binary logs, correlate across…

  • validate_fileDeterministic checks on a generated file

    Deterministic checks on a file you (or someone) just wrote: JSON/YAML/XML parse, CSV column-count consistency, JSON Schema conformance, broken relative links/anchors/images in Markdown/HTML, encoding/BOM/NUL/mixed line endings. USE WHEN: after generating or editing JSON/CSV/YAML/HTML/Markdown, "is this file valid", "check the links in this README", before handing a file to another tool or person. PREFER OVER: re-reading your own output to eyeball it, or setting up a linter for one check. A language toolchain (tsc, eslint, pytest) is the right tool for source code — this does not run it. DOES N…

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Last commit (this folder)
Oct 1, 2026 (28 days ago)
Last release
Oct 1, 2026 (28 days ago)

From GitHub (fetched Oct 24, 2026).

Details

Registry name
io.github.Warddamn/tiny-context
Version
0.3.0
Auth
No auth
Packages
mcpb https://github.com/Warddamn/tiny-tools/releases/download/context-v0.3.0/tiny-context-0.3.0-darwin.mcpbmcpb https://github.com/Warddamn/tiny-tools/releases/download/context-v0.3.0/tiny-context-0.3.0-linux.mcpbmcpb https://github.com/Warddamn/tiny-tools/releases/download/context-v0.3.0/tiny-context-0.3.0-win32.mcpb
License
MIT
Repository
github.com/Warddamn/tiny-tools
Website
github.com/Warddamn/tiny-tools/tree/main/packages/context#readme
First seen
Oct 24, 2026
Last checked
Oct 24, 2026
Source
Official MCP Registrygithub-graphql

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tiny-context — efficient file tools by AVRG3 MCP server. Agent Mart. https://agentmart.dev/connectors/warddamn-tiny-context (last updated 2026-10-24)