# tiny-context — efficient file tools by AVRG3 (mcpb · tiny-context-0.3.0-win32.mcpb) Local document queries, saved extraction profiles, spreadsheet SQL, logs and keyed JSON changes. - Trust score: 50/100 (low) - Change this week: −2 - Registry status: active - Liveness: live - Owner verified: no - Last scored: 2026-11-05 ## Components - mcpb · `tiny-context-0.3.0-darwin.mcpb`: 5/100, [markdown](https://verifymcp.io/servers/warddamn-tiny-context/https-github-com-warddamn-tiny-tools-releases-download-context-v0-1-1-tiny-conte.md), [page](https://verifymcp.io/servers/warddamn-tiny-context/https-github-com-warddamn-tiny-tools-releases-download-context-v0-1-1-tiny-conte) - mcpb · `tiny-context-0.3.0-linux.mcpb`: 5/100, [markdown](https://verifymcp.io/servers/warddamn-tiny-context/https-github-com-warddamn-tiny-tools-releases-download-context-v0-1-1-tiny-conte-2.md), [page](https://verifymcp.io/servers/warddamn-tiny-context/https-github-com-warddamn-tiny-tools-releases-download-context-v0-1-1-tiny-conte-2) - mcpb · `tiny-context-0.3.0-win32.mcpb`: 50/100 (this document), [markdown](https://verifymcp.io/servers/warddamn-tiny-context/https-github-com-warddamn-tiny-tools-releases-download-context-v0-1-1-tiny-conte-3.md), [page](https://verifymcp.io/servers/warddamn-tiny-context/https-github-com-warddamn-tiny-tools-releases-download-context-v0-1-1-tiny-conte-3) ## Channel facts - Registry: `mcpb` - Package: `https://github.com/Warddamn/tiny-tools/releases/download/context-v0.3.0/tiny-context-0.3.0-win32.mcpb` - Transport: `stdio` - SHA-256: `2b75baa5b942dd4b380f7b356ec0dfdbd6a532434e505bc2338f70ed32f91006` ## Trust breakdown How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog) Scored 2026-11-05. - **Supply Chain Security**: 0/100 - No malware scan is available for this kind of package: the supply-chain vendors we use do not cover it. This is a permanent gap in our coverage, not a finding about the package. - Known CVEs could not be checked: we found no dependency list to check in this bundle: either it runs a compiled binary, whose bundled manifests we do not read, or none of the package.json, requirements.txt, pyproject.toml or uv.lock files it ships for its runtime declares a dependency we can read (a requirements.txt that only points at a setup.py project, a local path, or a nested requirements file we cannot follow counts as none). - Install-script risk not yet assessed. - Dependency health could not be checked: we found no dependency list to check in this bundle: either it runs a compiled binary, whose bundled manifests we do not read, or none of the package.json, requirements.txt, pyproject.toml or uv.lock files it ships for its runtime declares a dependency we can read (a requirements.txt that only points at a setup.py project, a local path, or a nested requirements file we cannot follow counts as none). - **Provenance & Transparency**: 45/100 - Source repository is publicly reachable at the declared URL. - Provenance check failed: no build-provenance attestation is published. - Clear OSI-approved license (MIT). - Actively maintained (last published 35 days ago). - Disclosure check failed: no security disclosure policy was found in the source repository. - **Schema Quality & AI Usability**: 60/100 - AI-judged instruction clarity (excellent). - Context-footprint check failed: tool/resource definitions use about 3918 tokens (~489/item across 8 items; 8 tools + 0 resources), over budget; trim descriptions and params. - Usage-examples check failed: none of the tools include examples. - **Stability & Change Management**: 90/100 - Stability observed for 27 of 30 days with no destabilising changes; credit accrues until the full window elapses. - **Tool Coverage**: 100/100 - 100% of tools have a non-trivial description (not blank, and not just the tool's name). - 100% of tool parameters carry a description. - **Tool Safety**: 100/100 - No prompt-injection markers were found in the server instructions, tool names or descriptions we captured. - We read all 8 captured tool definition(s), and no name or description among them implies an irreversible operation. - An AI judge read all 9 captured unit(s) of tool text and found none that tries to manipulate the model reading it. - **Capabilities**: 100/100 - Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28. **Unverified: 1 category.** A category scored 0 because we could not verify it: a data source with nothing on this package, evidence we could not reach, or a check we could not run. We only credit what we can confirm. ## Install ### How do I install the tiny-context — efficient file tools by AVRG3 MCP server? tiny-context — efficient file tools by AVRG3 ships as an MCPB bundle, a single file you download and open in an MCP host that supports MCPB bundles, such as Claude Desktop. The host reads the launch command from the bundle's own manifest, so there is no command to copy. Before opening it, check the file's SHA-256 matches the one the MCP registry declares for it, 2b75baa5b942dd4b380f7b356ec0dfdbd6a532434e505bc2338f70ed32f91006; the commands to do that are on this page. If it does not match, do not open it. - Download bundle: `https://github.com/Warddamn/tiny-tools/releases/download/context-v0.3.0/tiny-context-0.3.0-win32.mcpb` - SHA-256: `2b75baa5b942dd4b380f7b356ec0dfdbd6a532434e505bc2338f70ed32f91006` ### Verify on macOS / Linux ```bash echo "2b75baa5b942dd4b380f7b356ec0dfdbd6a532434e505bc2338f70ed32f91006 tiny-context-0.3.0-win32.mcpb" | shasum -a 256 -c ``` ### Verify on Windows (PowerShell) ```powershell (Get-FileHash -Algorithm SHA256 .\tiny-context-0.3.0-win32.mcpb).Hash -eq "2b75baa5b942dd4b380f7b356ec0dfdbd6a532434e505bc2338f70ed32f91006" ``` ## Changelog Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims. ### 2026-11-04 (score 50, −2) - [functional] Stability: pass → 0.87 ### 2026-10-29 (score 52, +1) - [security] Stability: 0.97 → pass ### 2026-10-27 (score 51, +1) No change was recorded against any check on this day. Stability & Change Management went from 90 to 93. That category is still filling its 30-day observation window: 27 days of observed history at the previous scan, 28 at this one. The score rises as the window fills, whether or not the server changes. ### 2026-10-25 (score 50, +1) No change was recorded against any check on this day. Stability & Change Management went from 83 to 87. That category is still filling its 30-day observation window: 25 days of observed history at the previous scan, 26 at this one. The score rises as the window fills, whether or not the server changes. ### 2026-10-22 (score 49, +1) No change was recorded against any check on this day. Stability & Change Management went from 73 to 77. That category is still filling its 30-day observation window: 22 days of observed history at the previous scan, 23 at this one. The score rises as the window fills, whether or not the server changes. ### 2026-10-20 (score 48, +1) No change was recorded against any check on this day. Stability & Change Management went from 67 to 70. That category is still filling its 30-day observation window: 20 days of observed history at the previous scan, 21 at this one. The score rises as the window fills, whether or not the server changes. ### 2026-10-18 (score 47, +1) No change was recorded against any check on this day. Stability & Change Management went from 60 to 63. That category is still filling its 30-day observation window: 18 days of observed history at the previous scan, 19 at this one. The score rises as the window fills, whether or not the server changes. ### 2026-10-16 (score 46, +1) No change was recorded against any check on this day. Stability & Change Management went from 53 to 57. That category is still filling its 30-day observation window: 16 days of observed history at the previous scan, 17 at this one. The score rises as the window fills, whether or not the server changes. ## MCP tools (8) ### `file_map` (~353 tokens) Outline 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 already known, query_file/read_section directly; mapping is optional. Read is fine — and sufficient — for a small plain-text file (< ~20 KB): just Read it; do not call file_map on a file you have already read. DOES NOT: return contents (use read_section), search inside files (use query_file), or parse code with a real parser (signatures are regex-based, so unusual syntax may be missed). EXAMPLE: file_map({ path: "/abs/project/src", depth: 2 }) · file_map({ path: "/abs/contract.pdf" }) RETURNS: an outline with locations (line / page / sheet / slide / ¶) that read_section accepts, counts and sizes, then a savings line. Input parameters: - `depth` (integer): Directory depth to show. Default 2, max 8. Ignored for files. - `path` (string, required): File or directory to outline. Accepts absolute paths, '~' paths and paths relative to the current directory. Example: '/abs/project/src'. Required. ### `query_file` (~453 tokens) Find 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 everything this tool would return; do not call it on that file. Grep is fine for an exact string in one plain-text file. DOES NOT: add anything to a file you have already read, use embeddings/semantic search (BM25 keyword ranking + exact-phrase boost), return whole files, or search binary formats other than the ones listed. EXAMPLE: query_file({ path: "/abs/contract.pdf", query: "termination notice", max_results: 5 }) RETURNS: ranked hits "#1 file · page 12, line 3 (Heading > Sub)" with a short excerpt each, files/passages scanned, skipped files with reasons, then a savings line. Input parameters: - `context_lines` (integer): Lines of context around each hit. Default 2, max 10. - `max_results` (integer): Passages returned. Default 8, hard cap 30. - `path` (string): One file (or glob) to search. Example: '/abs/docs/contract.pdf'. Use `paths` for several. - `paths` (array): Several files or globs to search and rank together. Example: ['/abs/docs/*.pdf', '/abs/notes.md']. - `query` (string, required): What to look for, in plain words or a phrase. Example: 'termination notice period'. Required. - `regex` (boolean): Treat `query` as a JavaScript regular expression instead of ranked keyword search. Default false. ### `read_section` (~405 tokens) Read 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), read whole large files (cap 8000 tokens — narrow the locator instead), or render images. EXAMPLE: read_section({ path: "/abs/contract.pdf", locator: { pages: "3-5" } }) · read_section({ path: "/abs/spec.md", locator: { heading: "Installation" } }) RETURNS: the section text with line/page/¶ markers, word count, a "truncated at N — continue with …" note when capped, then a savings line. Input parameters: - `locator` (object, required): Exactly what to read: {heading} | {pages} | {lines} | {paras} | {sheet, range} | {slide}. Use a known location directly, or find it with file_map/query_file. Example: { pages: '3-5' }. Required. - `max_tokens` (integer): Cap on returned text (≈ bytes/4). Default 2000, max 8000. When hit, the response says how to continue. - `path` (string, required): File to read from. Accepts absolute paths, '~' paths and paths relative to the current directory. Example: '/abs/contract.pdf'. Required. ### `query_table` (~548 tokens) Query 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 MB, DuckDB memory 256 MB, worker deadline 15s (timeout_ms up to 60s). Explicit out creates a new CSV without overwriting. DOES NOT: modify the file, join several files (one file = one table), or return more than 200 rows in-context (use `out` to write the full result to CSV). EXAMPLE: query_table({ path: "/abs/sales.csv", sql: "SELECT region, SUM(total) FROM t GROUP BY 1" }) · query_table({ path: "/abs/sales.csv", sql: "DESCRIBE t" }) RETURNS: a markdown table of up to max_rows rows, column names/types, total result rows, the written file path when `out` is set, then a savings line. SQL errors include the table's columns and types so the next attempt succeeds. Input parameters: - `max_rows` (integer): Rows returned. Default 50, hard cap 200. The total row count is always reported. - `out` (string): Write the full result to a new CSV (64 MB export cap; existing files are never overwritten). Example: '/abs/out/by-region.csv'. - `path` (string, required): CSV, TSV, Parquet or XLSX file. Accepts absolute paths, '~' paths and paths relative to the current directory. Example: '/abs/sales.csv'. Required. - `sheet` (string): XLSX only: sheet name to query. Default: first sheet. - `sql` (string, required): One read-only DuckDB SELECT (WITH allowed) or DESCRIBE against table `t`; no external files or commands. Example: 'SELECT region, SUM(total) AS total FROM t GROUP BY 1 ORDER BY 2 DESC'. Required. - `timeout_ms` (integer): Query worker deadline in milliseconds. Default 15000, maximum 60000. Example: 5000. ### `summarize_log` (~391 tokens) Cluster 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 files, or explain root cause (it shows structure and timing so you can). EXAMPLE: summarize_log({ path: "/abs/logs/app.log", focus: "errors", since: "2h" }) RETURNS: totals + time span + level counts, a bucketed timeline (all vs. focused lines), top clusters "#1 ×812 ERROR 10:41→10:52