Skip to main content
Glama

furl_retrieve

Expand compressed data by hash to get the original content, search all stored entries, or project specific fields, lines, or rows.

Instructions

Retrieve original uncompressed content by hash. Use this when you need full details from previously compressed content. The hash comes from furl_compress results or from compression markers like [N items compressed... hash=abc123]. Two extra modes: (1) OMIT hash and pass query to search across ALL stored entries (returns ranked hash/score/preview matches to retrieve individually); (2) pass hash with pattern/fields/line_range, or a select_field row-filter (keep the rows of a JSON array by exact value or numeric range), to project just part of the original. Filters cannot be combined with query. Examples: furl_retrieve(hash) -> the whole original; furl_retrieve(hash, pattern="ERROR") -> only the matching lines; furl_retrieve(hash, select_field="id", select_equals=42) -> the rows where id==42.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rawNoReturn each matched row byte-identical to its source bytes instead of a re-serialized, pretty-printed copy — for hashing, diffing, or signature checks where the exact formatting must survive. Requires select_field (only a row-select yields whole source rows) and cannot be combined with fields (a projection has no source span). Every returned row is byte-exact; the rows are rejoined with fresh JSON array punctuation, so the blob as a whole is not a contiguous slice. If more rows match than 'limit', a single trailing {"__ccr_truncated__": ...} object is appended as a synthetic marker (NOT a source row); strip that one element by its key before hashing, or raise 'limit' to avoid truncation. Default false keeps the re-serialized output.
hashNoHash key from compression (e.g., 'abc123' from hash=abc123). Omit to search across all entries via 'query'.
limitNoMax rows returned by a select_field row-select OR a fields projection; a positive integer. A select without an explicit limit defaults to 1000; a fields projection without a limit is unbounded. When more rows match than the limit, only the first 'limit' ship plus one explicit truncation-marker row. It does not bound a pattern or line_range window, which line_range bounds instead.
queryNoSearch query. WITH a hash: return only items in that entry matching the query. WITHOUT a hash: full-text search (BM25-ranked) across every stored entry, returning top matches as hash/score/preview. Mutually exclusive with pattern/fields/line_range.
fieldsNoFor a JSON-array original: project only these keys out of each object element (requires a hash, no query). Errors if the original is not a JSON array. Cannot be combined with pattern/line_range; composes with select_field (projects the columns of the kept rows).
patternNoRegex applied line-by-line to the full original (requires a hash, no query). Returns matching lines (prefixed with 1-based line numbers) plus 'context_lines' lines of surrounding context. Invalid regex returns an error.
line_rangeNo[start, end] 1-based inclusive line window over the full original (requires a hash, no query). Either bound may be null for an open end. Composes with 'pattern' (the range is applied first).
select_maxNoNumeric-range mode: keep rows whose select_field is a number <= select_max (inclusive; open upper bound when omitted). Must be >= select_min. Mutually exclusive with select_equals.
select_minNoNumeric-range mode: keep rows whose select_field is a number >= select_min (inclusive; open lower bound when omitted). A row whose field is missing or non-numeric is skipped, never an error. Mutually exclusive with select_equals.
select_fieldNoRow-select over a JSON array of objects (requires a hash, no query): the field/column name to match on. It anchors the whole select family — select_equals / select_min / select_max / limit are honored ONLY alongside select_field (any of them without it is an error). Reads a top-level JSON array of objects OR a JSON object with exactly one dominant inner array (e.g. a '{metadata, traceEvents:[...]}' trace). Composes with 'fields'; cannot be combined with pattern/line_range or query.
context_linesNoLines of context to include on each side of a 'pattern' match (default 0, max 50).
select_equalsNoEquality mode: keep rows whose select_field equals this JSON scalar (string/number/boolean/null; a list or object is rejected). Bool-safe — true never matches the number 1. Mutually exclusive with select_min/select_max.
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the burden of behavioral disclosure. It details three operating modes, states that filters cannot combine with query, and gives illustrative outputs ('returns ranked hash/score/preview matches', 'only the matching lines'). It does not explicitly assert read-only/non-destructive status, but the word 'retrieve' and the context of accessing previously compressed content make that clear.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense but well-structured: core purpose in the first sentence, then two numbered extra modes, then examples. Every sentence adds functional value or constraints; there is no filler. The length is appropriate for a tool with 12 parameters and three usage modes.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite complexity and no output schema, the description is complete: it covers full retrieval, search mode, and projection modes, shows expected outputs for each, and mentions key constraints (filter/query exclusivity). It also references the source of the hash ('from furl_compress results or compression markers'), giving enough context to use the tool effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description adds high-level parameter usage beyond the schema by explaining combinations (e.g., omitting hash enables search; select_field anchors the row-filter family) and gives concrete examples like 'furl_retrieve(hash, select_field="id", select_equals=42) -> the rows where id==42,' which clarifies parameter interactions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb+resource: 'Retrieve original uncompressed content by hash.' It immediately states the core purpose and distinguishes the tool from siblings like furl_compress, furl_stats, furl_purge, and furl_list by focusing on retrieval. Concrete examples (e.g., 'furl_retrieve(hash) -> the whole original') reinforce the exact behavior.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says 'Use this when you need full details from previously compressed content,' giving a clear context for use. It also explains two alternative modes (query search, projection) and warns that filters cannot be combined with query, but it does not explicitly name sibling tools like furl_search as alternatives for when not to use this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/omar-y-abdi/furl-ctx'

If you have feedback or need assistance with the MCP directory API, please join our Discord server