mdbkit 0.3.0

Offline toolkit for MongoDB 4.4+ structured logs: log analysis, slow-query shapes, connection churn, and deterministic index advice. A spiritual successor to mtools' log tools.

mdbkit

An offline toolkit for MongoDB structured logs — log analysis, slow-query shapes, connection churn, and deterministic index advice.

A spiritual successor to mtools' log tools (mloginfo, mlogfilter) for the structured JSON log format MongoDB has used since 4.4 — the format mtools never supported. Built for DBAs and ops engineers running self-managed MongoDB 4.4 / 5.0 / 6.0 / 7.0 / 8.0.

Privacy by design: mdbkit never makes a network call. It reads log files (or stdin) and writes to stdout. No telemetry, no phoning home, no cloud. Your logs never leave your machine. It is safe to run on air-gapped database hosts.

Why

MongoDB 4.4 switched to structured JSON logging, and the beloved mtools log commands stopped working — the issue has been open since 2020. Meanwhile, index recommendations from MongoDB's Performance Advisor require a paid Atlas tier or Cloud/Ops Manager. If you run Community Edition on your own infrastructure, you're back to reading raw JSON logs with grep and jq.

mdbkit fills that gap: a single, dependency-free CLI that turns structured logs into answers.

Try it in 30 seconds

No MongoDB required — mdbkit demo writes a realistic log with a real incident in it:

pip install mdbkit
mdbkit demo --with-extras -o demo.log

mdbkit loginfo demo.log
mdbkit queries demo.log
mdbkit triage demo.log --window 0 --no-sysprobe
mdbkit advise demo.log --indexes indexes.json --schema schema.json

You will see a connection storm, a replica set election, an index build, and a collection scan burning 47 million document reads — then the candidate index that fixes it.

Install

Recommended on any Linux/Mac/Windows:

pip install mdbkit

Ubuntu 20.04 / Debian / Amazon Linux 2 (Python 3.8 hosts):

# Step 1: install pipx (manages isolated Python tool environments)
sudo apt install pipx        # Ubuntu/Debian
# or: sudo dnf install pipx  # RHEL/Rocky/Amazon Linux

# Step 2: install mdbkit
pipx install mdbkit

# Step 3: if pipx is not on your PATH yet
pipx ensurepath && source ~/.bashrc

If you get "externally-managed-environment" on modern Ubuntu (23.04+):

pip install mdbkit --break-system-packages

Air-gapped database hosts (no internet access):

# On a connected machine, download the wheel file
pip download mdbkit -d ./wheels

# Copy the ./wheels folder to the database host, then run
pip install --no-index --find-links ./wheels mdbkit

Upgrading to a newer version:

pip install --upgrade mdbkit      # if installed with pip
pipx upgrade mdbkit               # if installed with pipx
mdbkit --version                  # confirm

mdbkit never updates itself and never checks for updates — it makes no network calls at all. Upgrades are always explicit.

Requires Python 3.8+. Zero runtime dependencies — safe to install on production hosts.

mdbkit is a Python package distributed via PyPI. It is not available via apt install, dnf install, or yum install — use pip or pipx.

Quick start

# Overall log summary: versions, restarts, connection counts, error/warning totals
mdbkit loginfo /var/log/mongodb/mongod.log

# Slow queries grouped by query shape (literals stripped), ranked by total time
mdbkit queries mongod.log
mdbkit queries mongod.log --sort scanRatio --limit 10 --json

# Columns: cumMs = time summed across ALL occurrences of that shape (not one
# query); docsEx = documents examined; scan = examined per doc returned;
# plan = the plan MongoDB chose (COLLSCAN / IXSCAN{fields} / +SORT)

# Connection churn by source IP, appName, and driver
mdbkit connections mongod.log

# Filter raw log lines (output stays valid logv2 JSON — chainable)
mdbkit filter mongod.log --slow 500 --component COMMAND --ns shop.orders
mdbkit filter mongod.log --severity E --last 20      # 20 most recent errors
mdbkit filter mongod.log --slow 200 --limit 50       # first 50 matches only

# Time ranges — with or without a timezone offset
mdbkit filter mongod.log --from 2026-07-01T08:00:00+04:00 --to 2026-07-01T09:00:00+04:00
mdbkit filter mongod.log --from 2026-07-01T08:00:00Z     # UTC
mdbkit filter mongod.log --from 2026-07-01T08:00:00      # log's own timezone
mdbkit filter mongod.log --from 2026-07-01 | mdbkit queries -

# Rotated/compressed logs work directly
mdbkit queries mongod.log.2.gz

Step 1 — Export your indexes and schema (recommended)

mdbkit never connects to your database directly. Instead it prints small mongosh scripts you run yourself, so you can inspect exactly what they do before running them. The exports contain field names and types only — no document values.

Generate the export scripts:

mdbkit export-script indexes > export_indexes.js
mdbkit export-script schema  > export_schema.js

Run them against your database (replace with your actual host, port, and credentials):

# Basic (local, no auth):
mongosh --quiet "mongodb://localhost/yourdb" export_indexes.js > indexes.json
mongosh --quiet "mongodb://localhost/yourdb" export_schema.js  > schema.json

# With authentication (typical production setup):
mongosh --quiet \
  --host your_db_host \
  --port 27017 \
  --username your_username \
  --password your_password \
  --authenticationDatabase admin \
  --eval "$(cat export_indexes.js)" > indexes.json

mongosh --quiet \
  --host your_db_host \
  --port 27017 \
  --username your_username \
  --password your_password \
  --authenticationDatabase admin \
  --eval "$(cat export_schema.js)" > schema.json

In these examples, replace yourdb with your actual database name (e.g. shop, myapp). The --authenticationDatabase is usually admin unless you use per-db auth.

Step 2 — Run index advice

# Basic (without index/schema context — still useful, but lower confidence):
mdbkit advise mongod.log

# Full (with context — sharper recommendations):
mdbkit advise mongod.log --indexes indexes.json --schema schema.json

# Focus on one collection (recommended for large logs):
mdbkit advise mongod.log --indexes indexes.json --schema schema.json --ns shop.orders

Sample output:

[1] shop.orders  —  confidence: HIGH
    query shape : {createdAt:gt, status:eq} sort:{createdAt:-1}
    candidate   : { status: 1, createdAt: -1 }
    evidence    : COLLSCAN observed in planSummary
    evidence    : examined 251,400 docs to return 73 (3444:1)
    caveat      : Every index adds write and storage overhead ...
    validate    : Re-run the query with .explain('executionStats') ...

With --indexes, mdbkit checks candidates against your existing indexes — flagging when an existing index should already cover the query (it flags, never auto-drops). With --schema, it warns about array (multikey) fields, low-cardinality booleans, and field-name typos, and adjusts confidence accordingly.

Incident triage (beta)

mdbkit triage /var/log/mongodb/mongod.log     # last 60 minutes (default)
mdbkit triage mongod.log --window 30          # last 30 minutes
mdbkit triage mongod.log --window 0           # whole file
mdbkit triage mongod.log --dbpath /data/db    # if auto-discovery misses it
mdbkit triage mongod.log --no-sysprobe        # analyzing a log copied off-host

Defaults to the last 60 minutes of log time, because triage is for incidents happening now or just finished. In one command:

• cluster health — this node's replica set role, every peer's last known state, heartbeat failures, and whether the node is still serving
• restarts, error clusters, election/stepdown events
• connection storms — with the peak minute and the top source IPs
• slow-query volume and the peak minute, so you know when it hurt
• COLLSCAN share of slow operations (the missing-index signal)
• the hot collection plus its top three query shapes inline
• index-build activity (a common cause of surprise load)
• slow checkpoints, cache eviction pressure, flow control
• disk / memory / CPU load, and the running mongod's RSS and uptime

When run on the database host, mdbkit finds dbPath automatically — from the log's startup line, or the running mongod process, or /etc/mongod.conf, or common defaults — so the disk check works even when the current log has no startup event. diagnostic.data lives inside the dbPath, so it is picked up automatically too: you only need --ftdc to point somewhere else, such as a directory copied off another host. All probing is stdlib-only (/proc, statvfs); no shell-outs, nothing leaves the machine.

Cluster health is derived entirely from the log — no connection to the database. It reports what the node last said about itself and its peers, which is the honest limit of an offline tool, and enough to answer "is this node serving, and what does it think of the others?"

Read-only: it never connects to the database, and every finding ends with a next step for a human to review. Detectors marked beta are pattern-matched and clearly labeled while broader validation is pending.

Explain-plan analysis

Got a slow query in hand rather than a log? Save its explain output and ask mdbkit what's wrong:

# in mongosh:  EJSON.stringify(db.orders.find({...}).sort({...}).explain("executionStats"))
mdbkit explain explain.json

You get the plan chain (SORT -> COLLSCAN), the examined/returned math, plain- English verdicts (full collection scan, blocking in-memory sort, weakly selective index, covered query), and — when the plan needs help — the same evidence-backed candidate index the advisor would produce. Works with find and aggregate explains, classic and SBE (6.0+) plans, and sharded winning plans.

Design principles

• Deterministic. Same log in, same advice out. Rules, not AI. Every recommendation shows its evidence and its rule of reasoning.
• Candidates, not commands. mdbkit never tells you to blindly run createIndex, and never advises dropping an index.
• Honest about uncertainty. Shapes seen once are labeled low-confidence; $or, $regex, $in and low-selectivity operators carry explicit caveats.
• Offline, always. No network code exists in this codebase.

What it reads

Any MongoDB 4.4+ structured log: mongod.log, mongos logs, rotated .gz files, or stdin (-). Slow-query lines ("msg":"Slow query") are logged by default for operations over slowms (100 ms); lower slowms or enable profiling level 1 to capture more:

db.setProfilingLevel(1, { slowms: 50 })

Pre-4.4 plain-text logs are detected and politely refused — for those, the original mtools still works.

Command reference

Every command reads files or stdin and writes to stdout. --help works on any command (mdbkit queries --help). Global: mdbkit --version.

All commands that read a log accept a path to a .log file, a rotated .gz file, or - for stdin.

---

mdbkit loginfo <log>

Overall log summary: server version, host, restarts, connections accepted, slow-query count, warning/error counts, and a per-component line breakdown.

Option	Description
--json	Machine-readable output

mdbkit loginfo /var/log/mongodb/mongod.log
mdbkit loginfo mongod.log.2.gz --json

---

mdbkit queries <log>

Slow queries grouped by query shape — literal values stripped, so the same query with different parameters is counted once.

Option	Default	Description
--sort FIELD	totalMs	Order by totalMs, count, mean, max, docsExamined, or scanRatio
--limit N	all	Show only the top N shapes
--min-ms N	0	Ignore operations faster than N milliseconds
--include-system	off	Include internal admin/config/local namespaces (hidden by default — they are server housekeeping, not your workload)
--report FILE		Write a shareable .md or .html report instead (see Shareable reports)
--json		Machine-readable output

Reading the columns:

Column	Meaning
cumMs	Time summed across all occurrences of that shape — not one query
mean / max	Per-occurrence average and worst case
docsEx	Documents examined, summed across all occurrences
scan	Documents examined per document returned. 1:1 is ideal; 3444:1 means a missing or weak index
plan	The plan MongoDB chose: COLLSCAN (no index), IXSCAN{fields} (index used), IDHACK (_id lookup), +SORT (in-memory sort). ? = the plan was not recorded on that line
shape	Fields and operators queried, with the sort

mdbkit queries mongod.log
mdbkit queries mongod.log --sort scanRatio --limit 10
mdbkit queries mongod.log --min-ms 500 --json

---

mdbkit connections <log>

Connection churn and who authenticated: totals, peak concurrent count, per-source-IP breakdown with first/last seen, the client applications and drivers, and a per-user table.

Option	Description
--json	Machine-readable output

mdbkit connections mongod.log

source ip   accepted  ended  first seen           last seen            appName
----------  --------  -----  -------------------  -------------------  ------------
10.20.9.77  220       0      2026-07-01 08:49:30  2026-07-01 08:49:30  checkout-api
10.20.4.11  4         1      2026-07-01 08:00:15  2026-07-01 09:29:30  OrderService

authenticated users
user          auth db  ok   failed  last authenticated   from
------------  -------  ---  ------  -------------------  -----------
svc_checkout  admin    221  0       2026-07-01 08:49:30  10.20.9.77
etl_batch     admin    0    5       2026-07-01 08:51:54  10.20.11.40

  etl_batch: 5 failed authentication(s) — last error: AuthenticationFailed

This answers the question that starts most access incidents: did that account connect, from where, and when last? If the log shows no authentication events at all, mdbkit says so — either auth is disabled, or the window contains no new logins because clients are reusing connections.

---

mdbkit filter <log>

Streams matching raw log lines to stdout. Output stays valid logv2 JSON, so it chains with other tools (including mdbkit itself).

Option	Description
--component NAME	COMMAND, NETWORK, REPL, STORAGE, INDEX, WRITE, QUERY, CONTROL, …
--severity S	I info, W warning, E error, F fatal
--ns NAMESPACE	Exact namespace, e.g. shop.orders
--slow N	Only operations with durationMillis >= N
--from TIMESTAMP	Lower time bound (inclusive)
--to TIMESTAMP	Upper time bound (inclusive)
--msg TEXT	Substring match on the message field
--limit N	Print only the first N matches
--last N	Print only the last N matches — usually what you want during an incident
--as-explain	Rebuild each matching slow query as a runnable mongosh .explain() command instead of printing the raw log line
--explain-script	With --as-explain, wrap in EJSON.stringify() plus usage comments so it can be saved as a .js file

Timestamp formats accepted by --from / --to:

2026-07-01T08:00:00+04:00     with an explicit offset (production logs)
2026-07-01T08:00:00Z          UTC
2026-07-01T08:00:00           no offset — read as the log's own timezone
2026-07-01 08:00:00           space instead of T
2026-07-01T08:00               minute precision
2026-07-01                     whole day

mdbkit filter mongod.log --severity E --last 20    # errors (most recent 20)
mdbkit filter mongod.log --severity F               # fatal — always investigate
mdbkit filter mongod.log --severity W --last 50     # warnings
mdbkit filter mongod.log --component REPL --msg election
mdbkit filter mongod.log --slow 500 --ns shop.orders --limit 50
mdbkit filter mongod.log --from 2026-07-01T14:30:00+04:00 --to 2026-07-01T15:00:00+04:00
mdbkit filter mongod.log --slow 100 | mdbkit queries -

From a slow query in the log to an explain plan, without hand-writing the query — --as-explain rebuilds the command that ran:

# See the actual commands behind your slowest operations
mdbkit filter mongod.log --ns shop.orders --slow 500 --last 3 --as-explain

# Or produce a runnable script, get the plan, and analyze it
mdbkit filter mongod.log --slow 500 --last 1 --as-explain --explain-script > q.js
mongosh --quiet --host your_db_host --username your_username \\
        --password your_password --authenticationDatabase admin \\
        --eval "$(cat q.js)" > explain.json
mdbkit explain explain.json

Rebuilt commands contain the real values from your log (not redacted shapes) — treat them as sensitive.

---

mdbkit advise <log>

Deterministic candidate index recommendations from observed slow-query shapes, using the ESR guideline (Equality → Sort → Range). Rules, not AI: the same log always produces the same advice.

Option	Default	Description
--indexes FILE		indexes.json from mdbkit export-script indexes — enables overlap checks against existing indexes
--schema FILE		schema.json from mdbkit export-script schema — enables field-type caveats and confidence adjustment
--ns NAMESPACE	all	Only advise on one namespace (recommended on large logs)
--limit N	10	Show only the top N recommendations (0 = all)
--min-ms N	0	Ignore operations faster than N milliseconds
--min-count N	1	Only advise on shapes seen at least N times
--include-system	off	Include internal admin/config/local namespaces
--json		Machine-readable output

Each recommendation carries a candidate key pattern, the evidence behind it, a confidence level, caveats, and a validation step. mdbkit never advises dropping an index — at most it flags an overlap to investigate.

mdbkit advise mongod.log
mdbkit advise mongod.log --indexes indexes.json --schema schema.json
mdbkit advise mongod.log --ns shop.orders --limit 3

---

mdbkit explain <file>

Analyzes a saved explain("executionStats") document: the plan chain, the examined-vs-returned math, plain-English verdicts, and — when the plan needs help — a candidate index from the same advisor engine.

Option	Description
--indexes FILE	Overlap check against existing indexes
--schema FILE	Field-type caveats
--json	Machine-readable output

Full example. Get a plan for a query and analyze it:

# 1. Capture the plan (adjust host/credentials for your deployment)
mongosh --quiet \\
  --host your_db_host \\
  --port 27017 \\
  --username your_username \\
  --password your_password \\
  --authenticationDatabase admin \\
  --eval 'EJSON.stringify(db.getSiblingDB("shop").orders.find({status:"open"}).sort({ts:-1}).explain("executionStats"))' \\
  > explain.json

# 2. Analyze it
mdbkit explain explain.json

# 3. Sharper, with your existing indexes and sampled schema
mdbkit explain explain.json --indexes indexes.json --schema schema.json

Don't want to write the query by hand? mdbkit filter ... --as-explain rebuilds it from the log for you (see the filter section above).

Legacy mongo shell and Compass output containing NumberLong(...), ISODate(...) or ObjectId(...) is accepted — mdbkit unwraps those automatically, so you do not have to re-export.

---

mdbkit triage <log>

"Triage" means: quickly work out what is wrong and what to look at first. Run this when something has gone wrong — or has just gone wrong — and you need one screen that says what happened, how bad it is, and where to look next. Defaults to the last 60 minutes of log time.

Option	Default	Description
--window N	60	Analyze the last N minutes of log time; 0 = the whole file
--dbpath PATH	auto	Override the data directory used for the disk check
--no-sysprobe	off	Skip local disk/memory/CPU probes — use when analyzing a log copied off the host
--ftdc PATH		diagnostic.data directory — adds CPU, memory, cache, queue and connection history from MongoDB's own recorder
--report FILE		Write a shareable .md or .html report instead of terminal output
--json		Machine-readable output

mdbkit triage /var/log/mongodb/mongod.log
mdbkit triage mongod.log --window 30
mdbkit triage mongod.log --ftdc /var/lib/mongodb/diagnostic.data
mdbkit triage mongod.log --report incident.html
mdbkit triage mongod.log --window 0 --no-sysprobe

---

mdbkit ftdc {summary|timeline|export} <path>

Decodes diagnostic.data — FTDC (Full-Time Diagnostic Data Capture), the metrics recorder every mongod already runs. It holds CPU, memory, WiredTiger cache, connection, queue and operation history for every node, with no monitoring agent installed and no database connection. It is compressed BSON, not encrypted; mdbkit decodes it offline.

Action	Description
summary	min / avg / max / last per metric, plus per-second rates for counters
timeline	Values bucketed over time — shows when something spiked
export	CSV to stdout, for a spreadsheet or your own tooling

Option	Default	Description
--last DURATION	4h	Analyze only the most recent window — 90m, 4h, 2d
--all	off	Analyze the entire history (see the performance note below)
--metric LABEL	all	Restrict to one metric (repeatable), e.g. --metric conns.current
--step SECONDS	60	Timeline bucket size
--from / --to		Explicit time bounds (same formats as filter)
--json		Machine-readable output

Performance note. diagnostic.data can hold weeks of per-second samples — a few hundred megabytes covering thousands of chunks and several thousand metrics each. Decoding all of it is CPU-bound and takes minutes, so these commands default to the last 4 hours and skip older chunks before decompressing them. On a 250 MB directory that is the difference between about a second and about a minute. Use --last/--from/--to to move the window, and --all when you really do want the whole history.

mdbkit ftdc summary /var/lib/mongodb/diagnostic.data
mdbkit ftdc timeline diagnostic.data --metric conns.current --step 300
mdbkit ftdc export diagnostic.data > metrics.csv

Metric labels include ops.* (insert/query/update/delete/getmore/command), conns.current, conns.available, queue.readers, queue.writers, cache.usedBytes, cache.maxBytes, cache.dirtyBytes, tickets.*, mem.residentMB, and on Linux sys.cpu.* and sys.mem.availableKB.

The data directory can be copied off the host and analyzed elsewhere — it contains metrics only, never document contents.

---

Shareable reports — --report FILE

triage and queries can write a self-contained report instead of printing to the terminal — for a ticket, a handover, or a post-incident review.

mdbkit triage mongod.log --report incident.html     # styled, self-contained
mdbkit triage mongod.log --report incident.md       # for tickets and PRs
mdbkit queries mongod.log --limit 20 --report slow-queries.md

The format follows the file extension: .html or .md.

Markdown output looks like this:

# MongoDB incident triage

*window 2026-07-01 08:10 -> 09:10  ·  generated 2026-07-01 09:12*

## Findings

- **[CRIT] Replica set instability** — 3 election/stepdown event(s) at 08:41:02, 08:58:14
    - Starting an election, since we've seen no PRIMARY in election timeout period
    - *next:* `Correlate with connection storms and slow checkpoints below`
- **[WARN] Connection storm** — 2 minute(s) at >= 60 new connections/min; peak 480 at 08:41
    - 10.2.1.7: 312 in the peak minute
    - *next:* `mdbkit connections <log>`
- **[OK] Errors** — No error/fatal severity lines in window.

The HTML version carries the same content with a dark, print-friendly stylesheet. It is fully self-contained: inline CSS, no JavaScript, no external assets or CDN references, so it opens on an air-gapped machine and sends nothing anywhere.

Reports contain the same information as the terminal output — query shapes and metrics, never literal values from your documents.

---

mdbkit demo

Generates a realistic MongoDB structured log so you can evaluate mdbkit — or run a live demo — without a cluster. Output is deterministic for a given seed, so a demo behaves identically every time, including on a projector.

Option	Default	Description
--scenario	mixed	healthy, incident, or mixed
--minutes N	90	How much log time to generate
--seed N	7	Same seed produces byte-identical output
-o, --out FILE	stdout	Write to a file
--with-extras	off	Also write indexes.json, schema.json and explain.json beside the log

mdbkit demo -o demo.log                          # 90 minutes, mixed
mdbkit demo --scenario incident --minutes 30 -o incident.log
mdbkit demo --scenario healthy -o quiet.log      # nothing wrong: the control case
mdbkit demo | mdbkit queries -                   # straight down a pipe

The incident scenario contains an index build, a connection storm from a single client, a replica set election, plan-executor errors, a slow WiredTiger checkpoint, and a burst of unindexed queries afterwards — the shape of a real bad afternoon.

---

mdbkit lab

Starts a disposable local MongoDB for testing, reproducing a slow query, or rehearsing a demo. This is the only command that starts external processes; see SECURITY.md for exactly how it is bounded.

Requires mongod on your PATH (and mongosh to initiate the replica set and seed data). Linux and macOS.

Action	What it does
start	Create and start a replica set, print the connection string and log paths
seed	Insert sample data and run a workload with deliberately interesting queries
status	Show ports, pids and whether each node is running
logs	Print the log file paths, ready to pipe into other commands
stop	Stop the nodes, keep the data
destroy	Stop and delete the lab (requires --yes)

Option	Default	Description
--dir PATH	~/.mdbkit-lab	Where the lab lives
--nodes N	3	Replica set size
--port N	28110	Base port — deliberately far from 27017
--slowms N	0	Log every operation, which is what makes the log worth reading
--standalone	off	Single node, no replica set
--docs N	50000	Documents inserted by seed
--yes		Confirm destroy

The full loop:

mdbkit lab start                    # 3-node replica set on 28110-28112
mdbkit lab seed                     # sample data + a mixed workload

mdbkit queries $(mdbkit lab logs | head -1)
mdbkit advise  $(mdbkit lab logs | head -1)

mdbkit lab destroy --yes            # remove everything

seed runs indexed point lookups alongside deliberately unindexed queries — an equality-plus-range-plus-sort with no supporting index, an aggregation that scans the collection, and updates whose predicate has no index — so the log immediately contains something worth analysing.

Safety. The lab binds to 127.0.0.1 only, refuses to use or delete any directory it did not create, and never touches a MongoDB it did not start. It is a laptop and scratch-VM tool, not a deployment tool.

---

mdbkit export-script {schema|indexes}

Prints a small mongosh script to stdout. mdbkit never connects to your database — you run these yourself, so you can read exactly what they do first. Both are read-only and export field names and types only, never document values.

mdbkit export-script indexes > export_indexes.js
mdbkit export-script schema  > export_schema.js

---

Roadmap

Terminal output is and will remain first-class — this tool is built for the Linux box the database actually runs on.

Shipped in v0.3: demo log generation and lab disposable clusters, on top of v0.2's FTDC decoding, incident triage, query reconstruction and shareable reports.

Next up:

• mdbkit compare before.log after.log — did the index actually help?
• Multiple log files and globs in one command, for rotated logs.
• Per-shape drill-down (mdbkit queries --shape N with full detail).
• Graduating the remaining beta detectors (checkpoints, eviction, flow control) once validated against real incident logs — see docs/TESTING-PLAYBOOK.md. Real logs very welcome.

mdbkit is validated against real-world structured logs (tens of thousands of lines) in addition to its synthetic test fixtures.

Bugs, feature requests, questions

Please use GitHub Issues — it keeps problems and fixes public so the next person can find them. Real-world log lines that parse wrongly are the most valuable bug reports of all (redact literals first!).

Security

mdbkit is offline by design: the codebase contains no network code, never executes or evaluates input, and treats every log line as untrusted data (strict JSON parsing only — shell constructors are never evaluated). See SECURITY.md for the reporting process.

Non-affiliation

mdbkit is an independent community project. It is not affiliated with, endorsed by, or sponsored by MongoDB, Inc. "MongoDB" is a registered trademark of MongoDB, Inc., used here only to describe compatibility.

License

MIT — see LICENSE.