agent-core-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| diff_textA | Compute an exact line-by-line diff between two texts using a longest-common-subsequence algorithm. Returns per-line operations (equal/del/ins) with line numbers plus added/removed/unchanged counts. Exact and reproducible; refuses oversized input rather than hanging. |
| hashA | Compute a cryptographic hash of a UTF-8 string. Returns hex and base64 digests plus the UTF-8 byte length. Supports sha256 (default), sha512, sha1, md5, and HMAC variants via hmacKey. Use for content fingerprints, deduplication and integrity checks. |
| json_validateA | Check whether a string is valid JSON. On failure returns the parser message plus the computed line and column of the error. On success returns the top-level shape. Distinguishes valid-but-empty-object from invalid. |
| json_queryA | Extract a value from a JSON document by path, e.g. "a.b[0].c" or "$.items[3].name". Reports |
| json_pickA | Resolve several paths against one JSON document in a single call. Cheaper than issuing many json_query calls when you need multiple fields. |
| text_statsA | Exact text statistics: Unicode code points, UTF-8 bytes, lines, non-empty lines, words, sentences, paragraphs, unique words, average word length and most frequent words. Word segmentation is Unicode-aware so non-Latin scripts are counted correctly. Use whenever a count must be exact. |
| date_calcA | Interval between two ISO-8601 dates in days, weeks, months, years, hours, minutes, seconds or businessDays (Mon-Fri). Months and years use true calendar arithmetic, not 30/365-day approximations. All math is UTC. |
| date_addA | Offset an ISO-8601 date by days, weeks, months, years, hours, minutes or seconds. Negative amounts subtract. Calendar-correct across month ends and leap years. |
| regex_extractA | Apply a regular expression and return every match with its index, numbered capture groups and named groups. Iteration and match counts are hard-capped so a pathological pattern cannot hang the host. The response includes a ReDoS risk assessment of the pattern. |
| regex_analyzeA | Statically analyse a regular expression for catastrophic backtracking (ReDoS): nested quantifiers, overlapping alternation inside repeated groups, backreferences under quantifiers, excessive wildcards. Returns a risk level and the specific reasons. The pattern is not executed. |
| fuzzy_matchA | Score every candidate string against a query using the Sorensen-Dice coefficient over character bigrams and return the best matches in descending order. Deterministic. Useful for deduplication, record linkage, typo-tolerant lookup and confirming which of several candidates was meant. |
| similarityA | Sorensen-Dice similarity of two strings, from 0 (no shared character bigrams) to 1 (identical). One deterministic comparison. |
| parse_tableA | Parse delimited text into a header plus rows, handling quoted fields, escaped quotes, embedded delimiters and embedded newlines (RFC 4180 style). If no delimiter is given, the most frequent candidate on the first line is chosen and reported back. Use instead of splitting on commas, which breaks on any real CSV. |
| convertA | Convert a value between units of length, mass, time or data size. Cross-family conversions are rejected rather than silently producing nonsense. Data sizes: kb/mb/gb are decimal (1000), kib/mib/gib are binary (1024). Supported units: m, km, cm, mm, mi, yd, ft, in, nmi, kg, g, mg, t, lb, oz, s, min, h, d, b, kb, mb, gb, kib, mib, gib. |
| base_convertA | Convert an integer string between bases 2 and 36 with arbitrary precision. Uses big-integer parsing, so values beyond IEEE-754 double precision (2^53) stay exact, which is exactly where naive conversion goes wrong. A leading 0b/0x/0o prefix is ignored. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
| contract | What this server does and does not do. |
TDQS
Scored across 15 tools
Each tool targets a distinct operation, and the few potential pairs are explicitly differentiated in the descriptions: json_query (single path) vs json_pick (multiple paths), date_calc (interval) vs date_add (offset), regex_extract (apply) vs regex_analyze (static ReDoS analysis), and fuzzy_match (many candidates) vs similarity (one comparison). An agent can reliably pick the right tool for each intent.
All names use consistent snake_case, mostly following a noun_verb or verb_noun pattern (json_validate, date_add, regex_extract, parse_table, base_convert). A few single-word nouns (hash, similarity, convert) break the strict action-oriented pattern slightly, but the set is uniformly readable.
Fifteen tools sit comfortably in the well-scoped range, and each one covers a genuinely distinct capability (hashing, diffing, JSON, dates, regex, similarity, delimited parsing, unit and base conversion). No tool feels redundant or filler.
As a general text/data utility toolkit it covers its sub-domains well: JSON validate/query/pick, date arithmetic both directions, regex matching plus safety analysis, similarity, parsing and conversions. Minor gaps remain within sub-domains (e.g. no JSON formatting/minify or general string encoding/decoding), but core workflows have no dead ends.