contest-mcp
This MCP server integrates AI assistants with N3FJP amateur radio logging software, enabling natural‑language control of logging, querying, radio settings, and more.
Logging QSOs: Automatically log a contact using the
logtool (sets callsign, runs dupe check, fills exchange, submits). Individually set or clear entry fields, and directly add records to the database bypassing N3FJP scoring.Log Search & Dupe Checks: Search recent QSOs by call, band, mode, DXCC, country, or confirmed status with
search. Perform no‑side‑effect dupe checks and query all‑time‑new/worked/confirmed entity status.Program Status & Queries: Get a snapshot (
status) or detailed info (query) including program version, QSO count, next serial, file paths, QSO rate, and current band/mode/frequency.Field Manipulation: Read/write individual entry box values by friendly name or raw ID via
fields; list all visible or all fields with current values.Band/Mode/Frequency Control: Change frequency, band, mode, or pause rig polling to allow manual entry using
bandmode.Database Operations: Insert records directly, delete specific records with a
WHEREclause, run raw SQL, reload records (checklog/openlog), and close the SQL connection. Safety guards prevent accidental whole‑database wipes (configurable viaN3FJP_ALLOW_DB_WIPE).Notifications: Enable/disable push notifications from N3FJP (field updates, enter/calltab, dupes) and drain buffered events on demand.
Escape Hatch: Send arbitrary raw TCP commands with
n3fjp_callfor features not yet wrapped by other tools.Diagnostics: Troubleshoot network connectivity without connecting to N3FJP using
diagnostics.Configuration & Safety: Adjustable API host, port, socket timeout; safety model supports read‑only, “needs approval” for writes, and default blocking of destructive operations. Includes agent skills for contest operating (QSO state machines, special‑case handling) and comprehensive API documentation.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@contest-mcpLog a QSO with call sign W1AW on 40m FT8, exchange 59 TN"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
n3fjp-mcp
An MCP server for logging amateur-radio QSOs to N3FJP logging software — Amateur Contact Log and the 100-plus N3FJP contest loggers — from MCP-aware clients such as Claude Desktop.
Every program in the N3FJP suite shares one TCP control API. n3fjp-mcp speaks
that protocol directly (Python's standard-library socket, no third-party
wrapper) and exposes it as a small set of logically-grouped MCP tools, so an
assistant can log contacts, read the log, run dupe checks, and manage band/mode
through plain language.
It is the logging half of an "operate → log" workflow; its sibling project
fldigi-mcp operates the radio.
Status: experimental (v0.3). Verified live against N3FJP's ARRL Field Day Contest Log, API version 2.2. The protocol is shared across the suite, but field sets vary per contest — confirm with the
fieldstool.
⚠️ Independent project — not affiliated with N3FJP
n3fjp-mcpis an independent, community project by Stefan Brunner (AE5VG), using the "N3FJP" name with the permission of its owner. It is not affiliated with, endorsed by, or supported by N3FJP Software / Affirmatech. Please direct all support questions for this app to its issue tracker — not to N3FJP. MIT licensed. "N3FJP" is the callsign and trademark of its owner.
Related MCP server: qrz-mcp
Highlights
Automatic logging — the headline
logtool runs the real N3FJP flow: set the call →CALLTAB(dupe check + previous-contact lookup) → set the exchange →ENTER, surfacing the dupe response and the number of records added.Broad coverage — read queries, field read/write, search/list, dupe and entity checks, band/mode/frequency, direct database operations, and opt-in push notifications, grouped into 9 tools (one permission each) plus an
n3fjp_callescape hatch for the long tail and future commands.Safe by design for a tool that can touch your log database:
Reads are marked read-only so clients can default them to Always Allow.
Writes (logging, band/mode) default to Needs Approval.
Destructive operations (add-direct, delete a record, raw SQL) additionally require
confirm=true.Whole-database wipes/overwrites are refused outright unless you flip a dedicated, off-by-default
N3FJP_ALLOW_DB_WIPEswitch.
Names match N3FJP — tools and fields mirror N3FJP's own terminology (Action
ENTER,CALLTAB, theTXTENTRY…boxes, Class/Section, etc.).No fragile dependencies — the only runtime dependency is the MCP SDK.
Requirements
To install the desktop extension (.mcpb):
An N3FJP program running, with Settings → Application Program Interface → "TCP API Enabled" checked (default API port
1100).
Claude Desktop's uv runtime supplies Python and the dependencies, so end users
do not install Python or uv themselves.
For development from source you additionally need Python 3.10+ and uv (and Node.js, only for the MCP Inspector).
Install
Easiest: one-click desktop extension
Download n3fjp-mcp.mcpb from the latest
release, then in Claude
Desktop go to Settings → Extensions → Advanced settings → Install Extension…
and choose the file. A short settings form asks for the host/port (defaults to
127.0.0.1:1100). No terminal, no Python, no uv to install.
👉 New to this? Follow the step-by-step install guide.
From source (development)
git clone https://github.com/sbrunner-atx/n3fjp-mcp.git
cd n3fjp-mcp
uv syncThen add it to Claude Desktop's config
(~/Library/Application Support/Claude/claude_desktop_config.json on macOS):
{
"mcpServers": {
"contest": {
"command": "uv",
"args": ["--directory", "/absolute/path/to/n3fjp-mcp", "run", "n3fjp-mcp"],
"env": { "N3FJP_HOST": "127.0.0.1", "N3FJP_PORT": "1100" }
}
}
}Restart Claude Desktop and ask "What's the N3FJP status?".
Try it with the MCP Inspector
uv run mcp dev src/n3fjp_mcp/server.pyTools
Each tool is one permission and takes an operation argument.
Tool | Default | Controls |
| read | snapshot: program, version, API version, QSO count, band/mode/frequency |
| read | program, qso_count, next_serial, log/settings/shared paths, qso_rate, band_mode_freq |
| read | read one entry box, or list visible / all fields with values |
| read | list recent, search, dupecheck (no side effects), entity status |
| approval |
|
| approval | change_freq, set_band, set_mode, ignore_rig_polls |
| approval | enable / disable push events, drain buffered events |
| approval | add_direct, delete a record, raw sql, checklog, openlog, sqlclose |
| approval | escape hatch — send any raw command, incl. future ones |
All write tools sit at the Needs Approval tier, so you can set them to Always Allow in the client for hands-off automation. The single exception is a whole-database wipe (see below), which is hard-blocked regardless.
The headline is log → log_qso:
log_qso call="W1AW" contest="field_day" exchange={"class":"2A","section":"CT"}This sets the call, fires CALLTAB (dupe check), fills the exchange, sends
ENTER, and reports records added plus any dupe detail.
Configuration
Variable | Default | Purpose |
|
| N3FJP API host |
|
| N3FJP API port (the suite's default) |
|
| Socket/response timeout, seconds |
|
| Danger. Allow whole-database delete/overwrite (raw SQL |
In the packaged desktop extension these appear as a settings form.
Safety model
Logging doesn't key a transmitter, so there is no transmit gate. The protection here is about your log database:
Read operations (
status,query,fields,search) are marked read-only — clients can default them to Always Allow.Write operations — logging (
log), band/mode (bandmode), notifications, and adding, editing, or deleting individual records (database), plus then3fjp_callescape hatch — all sit at the Needs Approval tier. There is no extra in-band confirmation, so you can set them to Always Allow in the client and let automation run hands-off.Whole-database operations — raw SQL that could delete or overwrite the entire log (
DROP,TRUNCATE, aDELETE/UPDATEwith noWHERE) — are the one exception: refused unlessN3FJP_ALLOW_DB_WIPEis on. This switch is separate from, and stricter than, the client's approval prompts, and carries a stern warning in the settings form. Back up your log before ever enabling it.
Wherever possible, n3fjp-mcp leans on N3FJP's own validation (it dupe-checks
and reports oddities) and surfaces those responses rather than re-implementing
them.
Remote / contest-station setups (N3FJP on another computer)
If N3FJP runs on the same computer as Claude Desktop (the common case), leave
N3FJP_HOST at 127.0.0.1 and you're done.
If N3FJP runs on a different computer, there's a catch: a sandboxed MCP
client (notably Claude Desktop) runs the connector so it can only reach
127.0.0.1, not LAN addresses — so putting N3FJP's LAN IP in the settings will
time out even though telnet to that IP works. Fix it with the standalone
mcp-host-bridge tool on the
client computer, then set the host to 127.0.0.1:
pipx install mcp-host-bridge # or download a binary from its releases
mcp-host-bridge install n3fjp --to 192.168.1.50 # knows n3fjp = port 1100; auto-startsManage it with mcp-host-bridge status n3fjp / uninstall n3fjp. Full details
are in docs/REMOTE-HOST.md and the
mcp-host-bridge README.
The diagnostics tool helps confirm whether you need it. Keep the link on a
trusted LAN — the API is unauthenticated.
Documentation
📻 A field-tested N3FJP API reference (free community resource)
Building this server meant reverse-engineering and live-verifying the N3FJP TCP API, including several places where today's API (v2.2) differs from the public 0.9 documentation. We've written that up as a complete, human-readable guide and are sharing it freely to give back to the community:
The N3FJP TCP API — A Field-Tested Reference (PDF) — transport, every command grouped by area, verified response examples, contest exchange fields, and a hard-won gotchas section (the API vs. networking ports,
CMD_NOT_FOUND, commands removed since 0.9, theCALLTABEVENTlookup, and whyENTERcan report 0 yet still log in networked mode).Machine-readable spec — the same information in a terse, structured command catalog suitable for code generation.
Corrections and additions are welcome — please open an issue or PR.
Project docs
Install guide and Test plan.
Field Day 2026 lessons learned — the full after-action report from running an autonomous BPSK31 Field Day station (class 2A, callsigns anonymized) with n3fjp-mcp + fldigi-mcp: the operating loop, special cases encountered live, and recommended improvements.
Skills
The skills/ directory contains agent skills — operating
procedures distilled from live on-air use — bundled with the repo and the
.mcpb package:
contest-operating — the contest QSO state machine (CQ → exchange → TU → log), the special-case playbook (QRM, garbled callsigns, doubling, no-copy repeats, callsign-only callers), and the verified N3FJP logging sequence with its known quirks. Field-proven during ARRL Field Day 2026.
The Operating Skills Field Guide
(PDF) documents this skill and its companion fldigi-operating from the
sibling fldigi-mcp — skills at
a glance, installation, a plain-language "first session" chapter for hams
new to Claude, the operating standard, the special-case playbook, and worked
examples transcribed from ARRL Field Day 2026.
To use with Claude Code / Cowork, copy the skill directory into your
~/.claude/skills/ (or a project's .claude/skills/). Pair it with the
fldigi-operating skill from fldigi-mcp for radio control.
Development
uv sync
uv run ruff check . # lint
uv run pytest # tests (no running N3FJP required)
python3 smoke_test.py 192.168.1.50 1100 # Phase 0: prove the link to N3FJPThe test suite covers the wire protocol, the operation maps and field catalog, type coercion, and the permission/confirm safety model; none of it requires a running N3FJP.
License
MIT © 2026 Stefan Brunner (AE5VG)
Available Tools
10 toolsbandmodeA
Change band, mode, and frequency before logging.
operations:
change_freq (value=Hz): set the frequency (and thus band) via the rig interface. Use suppress_mode_default=true to keep the current mode rather than letting CW/phone segments flip it.
set_band (value=band, e.g. "20"): write the band box (rig interface OFF only).
set_mode (value=mode, e.g. "DIG"): write the mode box (rig interface OFF only).
ignore_rig_polls (value=bool): pause rig polling so band/mode boxes can be written while a rig is connected. Remember to set it back to false.
Always make sure the program is on the correct band and mode before ENTER.
| Name | Required | Description | Default |
|---|---|---|---|
| value | No | ||
| operation | Yes | ||
| suppress_mode_default | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses behavioral traits such as the dependency on rig interface state, the effect of ignore_rig_polls (pausing polling), and the side effect of CW/phone segment flipping. The caution to reset ignore_rig_polls to false shows awareness of state management.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a one-line purpose followed by a clear bullet list of operations. Each sentence adds value without redundancy. The front-loaded purpose and logical grouping make it easy to scan. It is concise yet comprehensive.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (multiple operations with conditional behaviors) and lack of output schema or rich annotations, the description is complete. It covers all operations, parameter formats, prerequisites, and a safety note. An agent can confidently invoke any operation based solely on this description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, but the description fully compensates by explaining each parameter's role per operation. It specifies acceptable values for 'value' (e.g., Hz, band like '20', mode like 'DIG') and the meaning of 'suppress_mode_default'. This adds critical semantic context beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Change band, mode, and frequency before logging.' It differentiates from sibling tools like 'log' and 'status' by focusing on rig configuration. The verb 'Change' and the specific resources (band, mode, frequency) provide unambiguous purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides detailed usage guidelines for each operation, including conditions (e.g., 'rig interface OFF only' for set_band, 'use suppress_mode_default=true to keep current mode'). It also includes a general caution to ensure correct band/mode before logging. This gives clear when-to-use and how-to-use instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
databaseA
Direct database operations on individual records.
These are ordinary writes (the Needs Approval tier — same as logging), so they can be globally allowed in the client for automation. The ONLY hard block is a whole-database wipe/overwrite, gated by N3FJP_ALLOW_DB_WIPE.
operations:
add_direct (fields={fldCall:..., fldBand:...}, exclude_dupes): insert a record directly, bypassing N3FJP's scoring. Prefer log's log_qso/ENTER.
delete (where="fldPrimaryID=123"): delete matching records. A missing or empty WHERE would clear the whole table and is refused unless N3FJP_ALLOW_DB_WIPE is on.
sql (sql="..."): run a raw SQL statement against the Access database. Only statements that could wipe/overwrite the whole database (DROP, TRUNCATE, unscoped DELETE/UPDATE) are refused unless N3FJP_ALLOW_DB_WIPE is on; scoped statements run normally.
checklog / openlog: ask N3FJP to reload new / all records.
sqlclose: close the SQL connection.
| Name | Required | Description | Default |
|---|---|---|---|
| sql | No | ||
| where | No | ||
| fields | No | ||
| operation | Yes | ||
| exclude_dupes | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description fully carries the burden of disclosing behavior. It details the safety tier (ordinary writes, approval), the hard block for whole-database wipe, and the behavior of each sub-operation (e.g., 'a missing or empty WHERE would clear the whole table').
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is relatively long but well-structured with clear sections, bullet points for operations, and separate warnings. It is organized for readability, though some sentences could be tightened. Overall, it earns its length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (5 parameters, multiple operations, no annotations, no output schema), the description provides comprehensive coverage: it explains all operations, parameter usage, behavioral constraints, and usage guidance. An agent has sufficient information to select and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 5 parameters with 0% description coverage. The description compensates by explaining the purpose of each parameter in the context of specific operations: e.g., fields for add_direct, where for delete, sql for sql operation, exclude_dupes for add_direct. This adds significant meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it performs 'Direct database operations on individual records' and lists specific sub-operations (add_direct, delete, sql, etc.), making the verb and resource obvious. It distinguishes itself from sibling tools like 'log' and 'query' by specifying that it bypasses scoring and allows raw SQL.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use alternatives, e.g., 'Prefer log's log_qso/ENTER' for add_direct. It also warns about conditions for safe usage, such as the need for N3FJP_ALLOW_DB_WIPE for destructive operations, and notes that certain operations are blocked without the environment variable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
diagnosticsARead-only
Host + network diagnostics for troubleshooting connectivity.
Does NOT connect to N3FJP. Reports the resolved N3FJP_HOST/PORT, this process's Python and hostname, and the host's network interfaces — so you can tell whether the process can even see the target's network (e.g. when running host-side vs. sandboxed).
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnlyHint annotation, the description discloses that it reports resolved N3FJP_HOST/PORT, Python version, hostname, and network interfaces, and importantly states it does not connect to N3FJP. This adds significant behavioral context beyond what annotations provide.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, front-loaded with the core purpose, followed by specifics and usage context. No unnecessary words; every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters, no output schema, but a clear readOnlyHint, the description fully explains the tool's behavior and output. It tells what the tool reports, what it does not do, and provides a use case. Complete for the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the description carries the full burden. It describes exactly what the tool reports, which adds all necessary meaning beyond the empty input schema. Baseline for 0 params is 4, and the description exceeds expectations.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs host and network diagnostics for troubleshooting connectivity. It explicitly differentiates from the sibling n3fjp_call by stating it does NOT connect to N3FJP, and the verb 'diagnostics' is specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context for when to use the tool (troubleshooting connectivity) and what it does not do (connect to N3FJP). However, it does not explicitly list alternatives or when not to use it, though the context is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
fieldsARead-only
Read entry-box (text field) values.
operations:
read (field=name): read one box.
fieldmay be a friendly name (call, rst_rcvd, class, section, name, …) or a raw control id (TXTENTRY…).visible: every field the current contest shows, with values.
all: every field (regardless of visibility), with values.
Derived fields (country_worked, cq_zone, itu_zone, continent, prefix) are readable here but are computed by N3FJP from the call — never write them.
| Name | Required | Description | Default |
|---|---|---|---|
| field | No | ||
| operation | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotation already declares readOnlyHint=true, and the description adds important context: it specifies the three operation modes and warns that derived fields (country_worked, etc.) are computed and should never be written. This goes beyond the annotation, though permissions or side effects are not mentioned.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured, using a clear list for operations. Every sentence adds value, and the main purpose is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only tool with no output schema, the description covers operations, parameter usage, and a warning. It does not describe the return format in detail except 'with values', but this is sufficient given the low complexity. Could be slightly improved with an example output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It thoroughly explains the 'field' parameter (friendly name or raw control ID, with examples) and the 'operation' parameter (read, visible, all). This adds substantial meaning beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool reads entry-box text field values and lists three specific operations (read, visible, all). It is a specific verb+resource combination and implicitly distinguishes from sibling tools like status or diagnostics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear guidance on when to use each sub-operation (read by field, visible for current fields, all for both visible and hidden). It includes a warning against writing derived fields. However, there is no explicit when-not or alternative comparison with sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
logA
Logbook entry: set fields, run Call-tab, and ENTER a QSO. The headline tool.
operations:
log_qso: the automatic-logging flow. Provide
call(and usuallyexchange, a dict of friendly field names → values, e.g. {"class": "2A", "section": "CT"}). Sets the call, runs CALLTAB (dupe check + lookups) unless calltab=false, sets the exchange, then ENTER. Returns the number of records added and any dupe response.set (field, value): write one entry box.
set_many (fields={...}): write several entry boxes.
calltab: run CALLTAB (after setting the call).
enter: log the current form. Returns records_added plus a
loggedboolean derived from the QSO-count delta / ENTEREVENT — trustlogged, not records_added, which can report 0 on success in networked mode. Do not retry when logged=true (creates duplicates).clear: clear the entry form.
focus (field): move focus to a box (e.g. to auto-fill default RST).
Tip: contest (e.g. "field_day", "cq_wpx") lets the tool warn if the
exchange is missing a field that contest needs.
| Name | Required | Description | Default |
|---|---|---|---|
| call | No | ||
| field | No | ||
| value | No | ||
| fields | No | ||
| calltab | No | ||
| contest | No | ||
| exchange | No | ||
| operation | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully discloses behaviors: return values (records_added, logged boolean), side effects (dupe creation on retry), conditional execution (calltab=false skips lookups), and reliability notes (trust logged over records_added).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-organized with bullet points for each operation and front-loaded purpose. It is slightly lengthy but every sentence adds value; minor redundancy could be trimmed.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (8 parameters, 6 operations, no output schema), the description covers behavior, return values, reliability tips, and contest validation. It lacks explicit error scenarios or full return format details for each operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides no descriptions (coverage 0%), but the description adds significant meaning for parameters like call, exchange (dict), calltab (default true), and contest. It could still be more systematic in documenting all parameter constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is the headline tool for logging QSOs, enumerates distinct operations (log_qso, set, calltab, etc.), and distinguishes itself from siblings like status and query as the primary logging tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use each operation and includes warnings (e.g., do not retry when logged=true). However, it does not explicitly advise against using this tool for non-logging tasks or when alternatives like search would be better.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
n3fjp_callA
Escape hatch: send any raw N3FJP command and return the parsed reply.
command may be a bare command id ("PROGRAM"), a full envelope
(""), or the inner form ("") — it is normalised
and CRLF-terminated for you. expect is the response id to wait for.
This reaches anything not surfaced by a group tool, including newer commands. Like the group tools, it runs at the Needs Approval tier; the only hard block is a raw SQL statement that could wipe/overwrite the whole database, which still requires the N3FJP_ALLOW_DB_WIPE switch.
| Name | Required | Description | Default |
|---|---|---|---|
| expect | No | ||
| command | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description does a good job disclosing key behaviors: command normalization, Needs Approval tier, and blocking destructive SQL unless a switch is set. Missing details on error handling or reply format but still strong.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is concise and well-structured: one-line purpose, then clear details. Every sentence adds value without unnecessary fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers command usage, safety, and relation to siblings. Missing details on return value structure, but since no output schema, it could be improved. Still sufficient for decision-making.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description adds essential meaning. Explains that 'command' accepts multiple formats and normalizes them, and 'expect' is the response ID to wait for. Additional examples would have made it perfect.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it is an 'escape hatch' for sending raw N3FJP commands and returning parsed replies. Distinguishes itself from group tools by noting it reaches anything not surfaced by them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says when to use (for commands not covered by group tools) and when not to (raw SQL that could wipe database requires a special switch). Provides context on command normalization and authorization tier.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
notificationsA
Opt-in push events from N3FJP (field updates, enter/calltab, dupes).
operations:
enable: turn on all-field-update notifications.
disable: turn them off.
drain: return and clear the buffered notification blocks received so far.
MCP is request/response, so events are buffered and you pull them with drain rather than receiving a live stream.
| Name | Required | Description | Default |
|---|---|---|---|
| operation | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavior. It reveals the buffering mechanism and that events aren't streamed in real-time. Missing details on authentication, rate limits, or failure modes, but covers key limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a brief statement followed by a bullet-like list of operations. It is reasonably concise, though the list could be more compact.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a simple schema with one parameter and no output schema, the description covers the essential behavior including buffering and operation semantics. Some edge cases (e.g., state after enable) are omitted, but overall complete for a notification management tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single 'operation' parameter has 0% schema coverage, so the description must fully explain its meaning. It does so by listing the three valid values (enable, disable, drain) and their effects, adding significant value beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it manages 'Opt-in push events from N3FJP' with three distinct operations (enable, disable, drain). This specific verb+resource combination distinguishes it from sibling tools like status or query.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explains when to use each operation and explicitly addresses the request/response buffering limitation, guiding the agent to use drain. However, no explicit when-not or alternatives to other tools are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
queryARead-only
Read-only program queries.
operations: program (name/version/API version), qso_count, next_serial, log_path, settings_path, shared_path, qso_rate (contest stats), band_mode_freq (current band/mode/frequency).
| Name | Required | Description | Default |
|---|---|---|---|
| operation | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description lists available operations, adding behavioral context beyond the readOnlyHint annotation. It does not contradict the annotation and provides useful specifics on what queries are possible, though it does not cover rate limits or auth requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with the sentence 'Read-only program queries.' However, the list of operations could be formatted for better readability, but it is still clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the description explains what queries are available, it does not specify the format or content of the return values. For a query tool with no output schema, the description could be improved by indicating what each operation returns.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% coverage (no description) for the only parameter 'operation'. The description compensates by listing all valid operation values, which is critical for correct invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Read-only program queries' and lists specific operations like program, qso_count, next_serial, etc. This distinguishes it from sibling tools like status, diagnostics, etc., which have different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied as read-only queries for program data, but no explicit when-to-use or when-not-to-use guidance is given. Sibling tools exist that could overlap (e.g., status, bandmode), but alternatives are not mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
searchARead-only
Search and list the log (read-only).
operations:
list (count, include_all): the most recent QSOs (primary fields, or every field with include_all=true).
search (call/band/mode/dxcc/country/confirmed, include_all, max_records): find matching QSOs. Prefer dxcc (ADIF number) over country (must match N3FJP's spelling exactly). mode is normalized to CW/PH/DIG.
dupecheck (call): is this call a dupe? Returns previous-contact detail or empty if new. (No side effects, unlike the log tool's calltab.)
entity (call, band, mode): all-time-new/worked/confirmed status.
| Name | Required | Description | Default |
|---|---|---|---|
| band | No | ||
| call | No | ||
| dxcc | No | ||
| mode | No | ||
| count | No | ||
| country | No | ||
| confirmed | No | ||
| operation | Yes | ||
| include_all | No | ||
| max_records | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, and the description reinforces 'read-only' and states 'No side effects' for dupecheck. It discloses behavior for each operation (e.g., returns previous contact detail or empty) with no contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with bullet points and a clear opening sentence. While it is somewhat lengthy due to covering four operations, each section earns its place. A slight reduction in verbosity could improve conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's 10 parameters and no output schema, the description thoroughly explains all operations, parameter semantics, and behavioral traits. It compares with siblings and covers edge cases (e.g., dupecheck's side-effect-free nature), providing sufficient context for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description fully compensates by explaining each parameter's role per operation (e.g., 'count, include_all for list', 'call/band/mode/dxcc/country/confirmed, include_all, max_records for search'). It adds semantic hints like normalizing mode and preferring dxcc over country.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly starts with 'Search and list the log (read-only)' and enumerates four distinct operations (list, search, dupecheck, entity). It explicitly states the tool's scope and differentiates among operations, giving each a concise purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use each operation (e.g., 'Prefer dxcc over country', 'mode is normalized to CW/PH/DIG'). It also directly contrasts dupecheck with the sibling tool's calltab ('No side effects, unlike the log tool's calltab'), offering clear alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
statusARead-only
Snapshot: program, version, API version, QSO count, band/mode/frequency, log path.
A quick health check that also confirms the connection and which N3FJP program/contest is loaded.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnlyHint annotation, the description clarifies it is a non-destructive health check that confirms connection and program loaded, adding useful context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, front-loaded with 'Snapshot', providing all key information efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description lists the returned fields (program, version, etc.), making the tool's response clear for a simple health check.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters, so baseline 4. The description does not need to add parameter meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it provides a snapshot of program details, version, QSO count, etc. However, it does not explicitly distinguish from the sibling 'diagnostics' tool, which might have overlapping purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implied usage as a health check to confirm connection and loaded program, but no explicit when-to-use or when-not-to-use guidance, nor alternatives mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
10 tool updates
v0.2.1- First observed
bandmode - First observed
database - First observed
diagnostics - First observed
fields - First observed
log - First observed
n3fjp_call - First observed
notifications - First observed
query - First observed
search - First observed
status
TDQS
Scored across 10 tools
Most tools have distinct purposes, but 'status' and 'query' both provide program information, causing slight overlap. Descriptions help disambiguate.
Tool names are all lowercase and descriptive, but they lack a consistent pattern (e.g., 'bandmode' vs 'n3fjp_call', no verb_noun structure).
10 tools cover the essential aspects of contest logging without being excessive or insufficient.
The surface is comprehensive: status, diagnostics, query, field reading, notifications, logging, band/mode control, search, direct database access, and a raw escape hatch cover all core needs.
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