Titen

Agent memory that runs with no API key, no LLM, and no embedding provider.
Every memory keeps its source, who may read it, and the evidence that contradicts it.

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Built with C.A.D.I.S Agent.

Try it in 30 seconds

No account, no key, no configuration — but the CLI runs on Bun 1.2 or newer, and refuses to start without it:

curl -fsSL https://bun.sh/install | bash   # skip if you already have Bun
npx titen-memory mcp

With no environment set, that opens or creates ~/.titen/memory.db, writes a real organization, workspace, project and owner into it, and serves MCP over stdio in-process — no HTTP hop, no key to paste, and no outbound network call. Retrieval is FTS5, so nothing needs an embedding provider or a model.

curl -fsSL https://titen.dev/install.sh | bash does the same in one step: it adds Bun when it is missing, then installs the titen command.

Point an agent at it:

claude mcp add --transport stdio --scope user titen -- npx -y titen-memory mcp

Already using @modelcontextprotocol/server-memory? Titen serves the same nine tool names with the same schemas, and answers memory://knowledge-graph too, so a client does not notice the swap. On the first local-mode start it imports your existing graph. Pass the old store's path, because that server writes beside its own install rather than in the directory you launch it from:

claude mcp add --transport stdio --scope user titen \
  --env MEMORY_FILE_PATH=/path/to/memory.jsonl -- npx -y titen-memory mcp

Without it Titen still checks the working directory, its node_modules, and npm's npx cache — and says on stderr when it found nothing, rather than starting empty in silence. Point titen at a served instance later by setting TITEN_MCP_URL and TITEN_API_KEY — full setup below.

Audit what any agent memory store has accumulated, including one Titen does not own:

npx titen-memory audit ./memory.json

What is different about it

• No provider, no key, no account. FTS5 lexical retrieval is the default operating point, not a fallback. Embeddings and model enrichment are opt-in projections that degrade cleanly when they are absent.
• No runtime dependencies. package.json declares none. What it needs is Bun and one SQLite file; everything else is the standard library and Web APIs.
• Drop-in for @modelcontextprotocol/server-memory. Eighteen tools — the nine titen_* plus the nine reference-server names — with search_nodes routed through real retrieval rather than a substring scan, and your existing memory.json imported on first run.
• It audits stores it does not own. titen audit reads a reference-server memory.json, a Mem0 export, or a Titen store, and reports duplicates, recall loops, secret patterns and staleness with per-item evidence you can check by hand.
• The benchmark publishes the losses. Two of the five pre-registered falsifiers fired against Titen, and they are printed on the chart below rather than left out of it.

Already running @modelcontextprotocol/server-memory?

That server had 106,662 downloads in the week of 31 July 2026 — it is the default memory for a large part of the MCP ecosystem, and it is deliberately minimal. Reading its published 2026.7.4 tarball: the store is one newline-delimited JSON file rewritten in full on every mutation, and a search is

graph.entities.filter(e => e.name.toLowerCase().includes(query.toLowerCase()) || ...)

String.includes on a lowercased needle. No tokenizer, no stemming, no ranking — results arrive in insertion order — no scoping or authorization, and no eviction, so the file grows without bound and every call is O(n) in the whole graph. Ask it "which service handles refunds" and it matches nothing unless that exact sentence is stored.

Titen answers the same nine tool names, with the same argument schemas, and the same memory://knowledge-graph resource, so a client does not notice the swap. What changes is underneath: search_nodes runs the real retrieval path — FTS5 with stemming, ranked best-first, and the vector index when one is configured — and every read is scoped to a subject and filtered by authorization before it is retrieved, not after.

Import is on first start; the switch is above.

Audit any agent memory store

Every published memory benchmark measures retrieval on a corpus somebody curated. The failure people actually report is on the write side: a store fills with copies of its own output. The one public audit of a production store found 97.8% of 10,134 entries were junk after 32 days. Nothing measures that.

npx titen-memory audit ~/.titen/memory.db        # a Titen store
npx titen-memory audit ./memory.jsonl            # @modelcontextprotocol/server-memory
npx titen-memory audit ./mem0-export.json --json # a Mem0 export

Five counts — exact duplicate, near duplicate, recall loop, secret pattern, stale — each with per-item evidence you can check by hand. No network, no model, no upload: it opens the path read-only and prints a report; sharing it is your decision. A store that lacks the signal a metric needs is reported as not measurable from this export, never as a failure. There is no composite score and there is no leaderboard.

The detection rules are published in audit rules. Titen's own numbers — including 17.9% duplicates and 96.7% stale in its own store, and a compatibility-surface defect the tool found in Titen itself — are in the self-report.

You author the claims

Titen's default memory model is caller-authored claims. consolidate() takes statements you wrote, each explicitly linked to a source observation you already recorded. Titen does not read a transcript and decide on its own what is worth remembering.

That is deliberate. Every claim has an author, a source, and a scope, which is what makes provenance, permission, conflict, and audit answerable at all. It is also a real cost, and it is the honest comparison point: systems that derive memory from raw dialogue do work Titen hands back to you.

Model-assisted derivation and reflection are implemented and ship in the package, but they are activation-gated and no candidate model has passed the gate — the best result on record is 65.56% against a 90% contract threshold. Treat them as unfinished work with a public gate, not as a feature you can simply switch on. The roadmap carries the current evidence.

The questions Titen answers

Agents connect through authenticated REST, Streamable HTTP MCP, the titen mcp stdio bridge, or the TypeScript SDK. Titen never treats retrieved memory as an instruction, and it does not run agent loops.

Measured against the field

On LongMemEval-S (MIT, externally authored, 500 instances, 246,930 turns), our own scorer, failures kept in the denominator, protocol pre-registered before each run. Full table and method at titen.dev/benchmark.

Every figure below names its condition, because the condition moves recall@1 by 63 points on the same corpus. Per-instance (scoped) gives each question its own ~50-session haystack — the single-subject shape a product actually serves. Pooled puts all 19,829 sessions in one unscoped store and asks the same 500 questions. These are two conditions of one corpus, not two measurements of one thing, and a number quoted without its condition is meaningless.

Condition A — per-instance (scoped)

This condition barely separates anything. recall@10 is 0.982 and saturated, with 2.2 points of spread across the serious lanes. Exactly one of the three paired sign tests reaches significance, and it does not say what it looks like it says:

• FTS+vector vs the dense control: 35/12/453, p = 0.0011 — significant.
• FTS+vector vs FTS-only: 27/17/456, p = 0.174 — the vector arm is not proven to be the cause of that win.
• FTS-only vs that control: 44/31/425, p = 0.165 — not significant.

We do not beat Mem0's LLM-free mode here. Mem0 infer=False scores 0.8667 on the shared n=60 subsample, and Titen FTS+vector against it is 3/4/53, p = 1.0 — indistinguishable. Its default infer=True mode spends 2,981 LLM calls to score lower (0.8333), so Mem0's own extraction bought nothing measurable here. Any cost claim must name the configuration it measured.

Answer accuracy is a flat null. With one reader pinned across every lane, eight pre-registered comparisons produce nothing significant (best p = 0.41). Retrieval significance does not transfer to answers.

Condition B — pooled, all 19,829 sessions in one store

¹ against Mem0's n=60 per-instance cell, not n=500.

Titen's zero-provider lane is significantly above every measured competitor at this condition — every pair below is written Titen-first, wins/losses/ties: 86/25/389 (p < 0.0001) against the fastembed control, 76/35/389 (p = 0.0001) against MemPalace, 59/27 (p = 0.0007) against Mem0 infer=False, 65/29 (p = 0.0003) against the router control. Those are the first significant lane-vs-lane retrieval separations this programme has produced on this corpus, at 363.8 s of ingest with zero provider calls against Mem0's 3,953 s and 205,641 embedding calls.

Two of the five pre-registered falsifiers fired against Titen, and they get the same prominence as that win.

• The prediction was wrong by more than 45 points. We pre-registered full-pool recall@1 at 0.70–0.85 and measured 0.246. LongMemEval-S personas share topics by construction, so pooling makes the store denser in cross-persona near-duplicates rather than sparser: all 377 rank-1 misses retrieved a cross-instance session, and zero retrieved a wrong session from the question's own haystack.
• Compile p95 is 864.9 ms against our own pre-registered 250 ms kill line, already crossed at the 10,000-session cell (430.8 ms). Published anyway, as promised.

Nobody's architecture escapes the pooled tax — MemPalace loses 64.0 points and the strongest dense control 68.0, against Titen's 63.4. And the vector arm reverses sign between the conditions: +2.0 points per-instance (unproven, p = 0.174) and −3.4 points pooled (0.212 against 0.246, p = 0.082), at 2.8x the compile latency after a 9,054 s index drain. Three embedding families now land 7.2–16.8 points below FTS-only at pooled density, so the vector arm is documented for scoped stores only. Full report: the pooled-store condition.

Scoping is the largest lever we have measured

Same corpus, same tarball, same 500 questions — one arm scoped to its subject, one not:

+63.4 points of recall@1 and 6.3x less latency. That is the measured value of authorization-before-retrieval, and the measured answer to "just scope by user_id" — scoping is the authorization layer, and Titen's runs before retrieval by construction.

The FTS-only curve across store shapes is 0.880 scoped, then 0.524 / 0.364 / 0.308 / 0.246 at 1k / 5k / 10k / 19,829 pooled sessions. Do not read the 0.880 without it.

The improvement cycle failed every gate

On 2026-08-08 we pre-registered a cycle to move those numbers — a candidate cap for latency, six ranking variants, and a third embedding family — and every gate in it failed. Nothing shipped. All six ranking variants failed their gate: term coverage −2.4, proximity −14.4, chunk-sum −11.8, combined −3.6, a local cross-encoder −1.2 at +642 ms per compile, RRF fusion +0.2 at p = 1.0. The five that were run against the scoped anchor regressed that too. The candidate cap was worth 4.5% of p95 against a predicted 30–60%, so the latency falsifier stands. The third embedding family scored 0.078. Full report: the pooled-improvement cycle.

That failure bought two things, both evidence rather than features:

• The shipped ranking is now ablation-backed, not incidental. Best-chunk aggregation beats sum-of-chunks by 11.8 points, and shipped BM25 order beats coverage, proximity, their combination, RRF fusion, and a local cross-encoder on both conditions.
• The +26.2-point top-10 ceiling is real, open, and unclaimed. Gold sits in the pooled top-10 at 0.508 against 0.246 at k=1. The cheap lexical class of fixes is spent; reaching it needs a signal that is not question-term overlap.

What survives every configuration argument is the dependency floor: Titen's FTS-only lane made zero LLM calls and zero embedding calls in both conditions. Mem0 without an LLM still needs an embedding provider. dependencies: {}, zero external imports in src/core/, and exactly two outbound calls in the whole codebase, both opt-in.

Other published losses: FTS-only recall@1 falls from 1.00 to 0.49 between 10³ and 10⁵ claims on a synthetic corpus — which understated the real-data degradation above — one process saturates one core at 10k claims, there is no reranking stage, and no external suite scores the governance and collaboration primitives at all.

Memory for a team, not a chatbot

A storage-only memory saves text. A retrieval-only memory embeds it and returns nearby passages. Both leave the caller to decide what is current, permitted, or true, and neither stops two agents from quietly claiming the same work.

Titen's Level 5 kernel turns source observations into evidence-linked, temporal claims and compiles only the context a caller is allowed to see. Level 6 joins that kernel to checkpoints, leases, handoffs, governance, audit, and signed federation.

Level 6 = evidence-grounded context + coordinated work + governance

Level 6 is Titen's product model, not an external certification. The distinction is observable in the API: memory and collaboration share one authorization, evidence, and audit boundary.

Project status

Titen is pre-1.0. Per SemVer clause 4, the public API is not yet stable. Below 1.0.0 the minor slot is the only breaking-change signal consumers get: 0.5.7 to 0.6.0 may break you, and ^0.5.0 does not match 0.6.0. Pin an exact version and read the changelog before upgrading.

Where the word stable appears around Titen — the npm latest dist-tag, "channel": "stable" in titen.dev/version.json, and titen version --check — it names the release channel: a deliberate release rather than a prerelease on next. It never describes API stability, and it is not a maturity badge. See versioning and channels.

The current release includes the memory kernel, REST API, MCP server, TypeScript SDK, collaboration tools, enterprise governance, signed federation, and the operator dashboard.

You can run Titen on Bun with SQLite or on Cloudflare Workers with D1. Semantic retrieval is optional: use sqlite-vec on Bun, or Vectorize and Workers AI on Cloudflare — verified live only on the maintainer's isolated the maintainer release stack stack, which is test production and not general availability (scope note). Titen runs in your own infrastructure.

Clients. Titen ships a TypeScript/JavaScript SDK, the titen CLI, and a minimal Python client in clients/python/. The Python client is one standard-library-only file covering observe → consolidate → compile → evidence, with a generic request for every other route. It is not published to PyPI: install it from a checkout with pip install ./clients/python, or vendor titen.py. There is no client for any other language — those callers use the authenticated REST API directly, and every route, scope, and error shape is in the API reference.

See the maturity matrix for detailed runtime evidence and remaining gates, or the changelog for release history.

Install and connect an agent

This section is the served deployment: a long-running instance with its own API keys, reachable over HTTP by more than one agent. If you only want memory for the agent on this machine, the 30-second path above is the whole setup and you can skip to optional semantic retrieval.

The local server needs Bun 1.2 or newer. The website installer adds Bun when needed, then installs the titen command for your current user:

curl -fsSL https://titen.dev/install.sh | bash
titen --version

Windows PowerShell:

irm https://titen.dev/install.ps1 | iex
titen --version

You can also run bun add --global titen-memory@latest. npm and pnpm global installs work when Bun is already on PATH.

The published package includes the current operator dashboard. After installing the CLI, run titen dashboard to serve that exact release's /dashboard/ assets; it does not enable live data or expose a listener beyond loopback.

1. Create the store

Run this once. Without --db, Bun service commands use the stable per-user store at ~/.titen/service.db regardless of the current directory:

titen bootstrap --org "My Org"

Save the organization ID, API key, and temporary dashboard password from the output. Titen stores only their hashes. The dashboard user is owner and must change its password at first login.

An existing release that used ./titen.db is never moved automatically. Keep using it explicitly with --db /absolute/path/to/titen.db, then use the same flag for serve, key administration, migration, and backup.

Create a separate revocable key for each agent host. Replace the organization ID and choose a stable principal name:

titen key create \
  --org-id org_replace_me \
  --principal agent-codex \
  --kind agent \
  --scopes "mcp:call,projects:create" \
  --trust asserted \
  --label codex

mcp:call includes write-capable memory and coordination tools. Do not share one key across every agent.

2. Start the service

titen serve

Open another shell and check readiness:

curl --fail http://127.0.0.1:8787/readyz
export TITEN_MCP_URL="http://127.0.0.1:8787/mcp"
export TITEN_API_KEY="paste-the-agent-key-here"

Keep the key in your shell, service environment, or secret manager. Never put it in a repository. If the agent runs in a container or on another machine, 127.0.0.1 points at that agent, not the Titen server; use a private HTTPS, Tailscale, or trusted tunnel URL instead.

3. Connect your agent host

Codex can connect to Titen's HTTP endpoint directly. It stores the environment variable name, not the key:

codex mcp add titen --url "$TITEN_MCP_URL" \
  --bearer-token-env-var TITEN_API_KEY
codex mcp get titen --json

Claude Code can launch the bundled stdio bridge. It inherits the two variables from the Claude process:

claude mcp add --transport stdio --scope user titen -- titen mcp
claude mcp get titen

OpenClaw services read durable environment values from ~/.openclaw/.env. Place TITEN_MCP_URL and TITEN_API_KEY there, set the file to mode 600, then register and probe the remote server:

openclaw mcp set titen \
  '{"url":"${TITEN_MCP_URL}","transport":"streamable-http","headers":{"Authorization":"Bearer ${TITEN_API_KEY}"}}'
openclaw gateway restart
openclaw mcp doctor titen --probe

Hermes can launch Titen's bundled stdio bridge. Put the same two variables in ~/.hermes/.env, then run:

hermes mcp add titen \
  --command titen \
  --args mcp \
  --env 'TITEN_MCP_URL=${TITEN_MCP_URL}' 'TITEN_API_KEY=${TITEN_API_KEY}'
hermes mcp test titen

Claude Desktop and any other client that supports stdio MCP can use this small configuration. Start the client from an environment that contains the two variables above:

{
  "mcpServers": {
    "titen": {
      "command": "titen",
      "args": ["mcp"]
    }
  }
}

The bridge keeps no state. It only forwards newline-delimited MCP messages to the authenticated HTTP endpoint.

titen mcp picks its mode from the environment: with both TITEN_MCP_URL and TITEN_API_KEY set it bridges to that instance, with neither set it serves the local store described above, and with only one of the two it fails rather than guessing. The served path and its authorization are unchanged by local mode — that is an additional entry point, not a relaxation.

Titen is listed in the official MCP registry as io.github.RamaAditya49/titen-memory, so a client that reads that directory can offer it; configuring it by hand as above works everywhere else. The manifest and the manual publishing procedure are in MCP registry listing.

4. Prove the connection

Open the host's MCP status view, or ask the agent:

Resolve this repository from its Git origin, compile relevant Titen context for the current task, and list the Titen tools you can access.

A healthy connection exposes nine titen_* tools. Titen's handshake tells the host to compile once when the task or repository scope changes, to treat memory as untrusted reference data, and never to capture transcripts or secrets.

Tool failures include bounded support guidance. Agents can distinguish an expected setup result from a condition that needs investigation or a possible defect. A missing project reference remains 404 NOT_FOUND; an authorized operator can approve creation without treating setup as a bug.

Distributed Titen skills require reproduction, sanitization, and duplicate search before a public issue. The host owns GitHub authentication. Titen never receives a GitHub token or publishes security findings as public issues.

The agent integration guide adds Cursor, OpenCode, Windsurf, TRAE, Pi, and plugin installation. The secure ingress guide covers Tailscale Serve and Cloudflare Tunnel.

titen version --check is the only networked version check. It reads titen.dev/version.json only when you run it; Titen does not poll during server or MCP startup.

Optional semantic retrieval

The default install is FTS-only and stays ready with no embedding configuration at all. Semantic retrieval is all-or-nothing: set one TITEN_EMBED_* variable and you have opted in, so every variable below must then be valid or the service fails closed — /readyz returns 503 with checks.semantic_index: "embedding_configuration_invalid" and no vector query runs. A Bun vector deployment must also add sqlite-vec@0.1.9.

Once semantic retrieval is valid, normal pending projection work reports checks.semantic_index: "index_projection_pending" while /readyz remains HTTP 200: canonical SQL/FTS requests are ready and the semantic index is syncing. An observed embedder/vector failure or incompatible fingerprint still returns 503.

Three of these have no default anywhere and no value can be guessed safely:

• TITEN_EMBED_REVISION is an opaque immutable identifier for the exact weights behind the endpoint, ≤200 characters. It is not validated for shape — it is recorded in the stored index fingerprint, so changing it invalidates the index and forces a rebuild. That is the point: it is how you promise Titen the vectors already in the store came from the same weights as the next query. A provider that cannot name an immutable revision should stay FTS-only.
• TITEN_EMBED_PROFILE selects the query/document input transform, and the accepted value is forced by the model id. Any model id containing embeddinggemma (case- and punctuation-insensitive) accepts only embeddinggemma-retrieval-v1; every other model accepts only raw-unit-v1. There is no way to run an EmbeddingGemma model on raw untransformed input, and no way to apply the EmbeddingGemma prompts to another model. A mismatch is configured_error, not a warning.
• TITEN_EMBED_MIN_COSINE has no shipped default. An unset variable reads as the empty string, which is rejected, so semantic retrieval fails closed rather than silently accepting weak matches. Titen ships no universal or pre-inspected threshold: derive it from a locked evaluation of that exact provider, model, revision, and profile. 0 is a valid, deliberate value meaning "accept every candidate the index returns and let ranking decide".

Worked EmbeddingGemma example — an OpenAI-compatible endpoint serving embeddinggemma at 768 dimensions:

bun add titen-memory sqlite-vec@0.1.9

TITEN_EMBED_BASE_URL=http://127.0.0.1:11434/v1 \
TITEN_EMBED_MODEL=embeddinggemma \
TITEN_EMBED_DIMS=768 \
TITEN_EMBED_REVISION=embeddinggemma-q4-2026-07-31 \
TITEN_EMBED_PROFILE=embeddinggemma-retrieval-v1 \
TITEN_EMBED_MIN_COSINE=0.32 \
bunx titen-memory serve

embeddinggemma-retrieval-v1 is the only profile that model id will accept. embeddinggemma-q4-2026-07-31 is a placeholder: substitute the immutable revision your provider reports, and treat any change to it as an index rebuild. 0.32 is a placeholder too — replace it with your own calibrated floor and record how you measured it. Verify with curl --fail http://127.0.0.1:8787/readyz; a healthy vector deployment reports capabilities.vector: "enabled".

The packaged vector path is verified on glibc Linux x64 with Bun 1.3.13; other platforms need their own ready, drain, and query smoke.

For backups, key rotation, containers, and durable service setup, use the Bun/VPS deployment guide.

Use the SDK

The SDK uses fetch and runs on Node 22+, Bun, Deno, and edge runtimes.

titen-memory is ESM-only — it has no CommonJS entry — so the consuming project must be ESM too. npm init -y writes "type": "commonjs", which is why the second line below is not optional: without it Node fails with SyntaxError: Cannot use import statement outside a module before it reaches any Titen code.

npm install titen-memory
npm pkg set type=module

Save this as titen-example.js and run node titen-example.js:

import { TitenClient } from "titen-memory";

const titen = new TitenClient({
  url: process.env.TITEN_URL ?? "http://127.0.0.1:8787",
  key: process.env.TITEN_API_KEY,
});

const subject = "release-runbook";
const observation = await titen.observe({
  subject_id: subject,
  kind: "imported_source",
  content: "The release runbook requires a rollback smoke test after deployment.",
  source: { type: "runbook", ref: "ops/release.md" },
  trust: "verified",
});

await titen.consolidate(subject, [
  {
    kind: "procedural",
    statement: "Run a rollback smoke test after deployment.",
    sources: [
      { observation_id: observation.observation_id, relation: "supports" },
    ],
  },
]);

const context = await titen.compile({
  subject_id: subject,
  task: "rollback smoke after deployment",
  max_tokens: 900,
});

console.log(context.items);

The script needs a running service and a key: start one with titen bootstrap --org "My Org" and titen serve, then export TITEN_API_KEY. In TypeScript the same file works unchanged as titen-example.ts on Node 22.18+ or Bun; write process.env.TITEN_API_KEY! there to satisfy strict null checks. Skipping npm pkg set type=module and naming the file .mjs/.mts also works — those extensions are ESM regardless of package.json.

max_tokens accepts 128 through 32,000. Every returned memory item includes untrusted: true; the client still owns prompt boundaries and action policy.

Python callers use clients/python/, which is not on PyPI and installs from a checkout. Any other language calls the REST API in the API reference directly.

Typed methods cover common agent operations. request() and requestRaw() cover the remaining authenticated JSON and streaming routes. Mutations accept an idempotencyKey for safe retries.

See the agent guide and API reference for request contracts and scope rules.

Architecture

One Web-Standards TypeScript core serves both runtimes:

Vectorize scope. Vectorize and Workers AI are implemented and verified live on the maintainer release stack, an isolated stack on the maintainer's own Cloudflare account, with scoped BGE-M3 retrieval, bounded repair, Cron, persistence, and rollback. That is test production and not a general-availability claim: no customer deployment runs it, and your account needs its own ready, drain, and query smoke before you rely on it. Without an AI/Vectorize binding a Worker stays ready and retrieval is lexical D1 FTS5. The maturity matrix holds the exact evidence.

Automatic model-assisted claim derivation and reflection are implemented as an opt-in capability with durable jobs, bounded validation, and separate readiness. They are not production-activated: no candidate model has passed the frozen activation gate, and the locked evaluation and real-runtime smokes are not recorded. Callers author evidence-linked claims explicitly, as described in You author the claims.

The base service does not require Docker, Redis, Postgres, a graph database, or a vector database. Authorization runs before retrieval, and every candidate is hydrated from canonical SQL before Titen returns it.

Read the architecture overview for component and failure boundaries. Cloudflare operators should start with the Cloudflare deployment guide.

Dashboard

The checked-in Astro client at /dashboard/ is a live fifteen-destination operator surface spanning memory, collaboration, operations, administration, governance, and Profile. Each person signs in with a username/password; the loopback adapter keeps the resulting short-lived key behind an opaque HttpOnly session and never writes either secret to browser storage. Bootstrap creates owner with a random temporary password, and Add User follows the same forced-first-change flow. A persistent SQL throttle limits password guessing across restarts. Optional WebAuthn passkeys use staged sessions and once-only recovery codes without blocking public API clients. API keys remain for agents, services, SDKs, and recovery. There is no fixture fallback when the service is disconnected or denies a request.

Each data area uses a task-specific table, list, or fact view. Select a record to open its inspector. Row actions operate on that exact record. The full authorized response remains available in a closed Technical payload disclosure for diagnosis.

The dashboard guide covers configuration and verification. Use the secure ingress guide for private Tailscale Serve access or Cloudflare Tunnel protected by Access.

For a packaged install, start the adapter from the same release:

TITEN_DASHBOARD_LIVE=true \
TITEN_DASHBOARD_AUTH=session \
TITEN_API_URL=http://127.0.0.1:8787 \
titen dashboard

Documentation

Development

The repository requires Node 22+, Bun 1.2+, and pnpm.

git clone https://github.com/RamaAditya49/titen.git
cd titen
pnpm install
pnpm test
pnpm check:workflow

Changes follow spec -> plan -> implement -> done. Read CONTRIBUTING.md before changing public behavior, storage, authorization, or runtime contracts.

Security

Keep Titen bound to 127.0.0.1. Remote agents should use a private network or a trusted TLS reverse proxy. When that proxy exposes /mcp, set TITEN_MCP_ORIGIN to its exact public origin. Use TITEN_SECRET_KEYS as the external encryption keyring for persisted webhook and federation signing secrets, and set TITEN_WEBHOOK_ALLOWED_HOSTNAMES before enabling outbound webhooks. The VPS security guide defines the formats and rotation procedure.

Do not report vulnerabilities in a public issue. Use GitHub Private Vulnerability Reporting and follow SECURITY.md. Never include real credentials or private memory content in a report.

License

Titen is licensed under the Apache License 2.0.